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Journal articles on the topic 'Inference Without Moments'

Author: Grafiati

Published: 1 June 2024

Last updated: 31 July 2025

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1

Zhang, Zhiyi. "Several Basic Elements of Entropic Statistics." Entropy 25, no. 7 (2023): 1060. http://dx.doi.org/10.3390/e25071060.

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Inspired by the development in modern data science, a shift is increasingly visible in the foundation of statistical inference, away from a real space, where random variables reside, toward a nonmetrized and nonordinal alphabet, where more general random elements reside. While statistical inferences based on random variables are theoretically well supported in the rich literature of probability and statistics, inferences on alphabets, mostly by way of various entropies and their estimation, are less systematically supported in theory. Without the familiar notions of neighborhood, real or compl

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Chernozhukov, Victor, Whitney K. Newey, and Andres Santos. "Constrained Conditional Moment Restriction Models." Econometrica 91, no. 2 (2023): 709–36. http://dx.doi.org/10.3982/ecta13830.

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Shape restrictions have played a central role in economics as both testable implications of theory and sufficient conditions for obtaining informative counterfactual predictions. In this paper, we provide a general procedure for inference under shape restrictions in identified and partially identified models defined by conditional moment restrictions. Our test statistics and proposed inference methods are based on the minimum of the generalized method of moments (GMM) objective function with and without shape restrictions. Uniformly valid critical values are obtained through a bootstrap proced

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Montiel Olea, José Luis, Mikkel Plagborg-Møller, and Eric Qian. "SVAR Identification from Higher Moments: Has the Simultaneous Causality Problem Been Solved?" AEA Papers and Proceedings 112 (May 1, 2022): 481–85. http://dx.doi.org/10.1257/pandp.20221047.

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Two recent strands of the structural vector autoregression literature use higher moments for identification, exploiting either non-Gaussianity or heteroskedasticity. These approaches achieve point identification without exclusion or sign restrictions. We review this work critically and contrast its goals with the separate research program that has pushed for macroeconometrics to rely more heavily on credible economic restrictions. Identification from higher moments imposes stronger assumptions on the shock process than second-order methods do. We recommend that these assumptions be tested. Sin

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Vendeville, Nathalie, Nathalie Blanc, and Claire Brechet. "A Drawing Task to Assess Emotion Inference in Language-Impaired Children." Journal of Speech, Language, and Hearing Research 58, no. 5 (2015): 1563–69. http://dx.doi.org/10.1044/2015_jslhr-l-14-0343.

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Purpose Studies investigating the ability of children with language impairment (LI) to infer emotions rely on verbal responses (which can be challenging for these children) and/or the selection of a card representing an emotion (which limits the response range). In contrast, a drawing task might allow a broad spectrum of responses without involving language. This study used a drawing task to compare the ability to make emotional inferences in children with and without LI. Method Twenty-two children with LI and 22 typically developing children ages 6 to 10 years were assessed in school during 3

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Hamsa, A. Abdullah. "Neuro-fuzzy inference system based face recognition using feature extraction." TELKOMNIKA Telecommunication, Computing, Electronics and Control 18, no. 1 (2020): 427–35. https://doi.org/10.12928/TELKOMNIKA.v18i1.12992.

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Human face recognition (HFR) is the method of recognizing people in images or videos. There are different HFR methods such as feature-based, eigen-faces, hidden markov model and neural network (NN) based methods. Feature extraction or preprocessing used in first three mentioned methods that associated with the category of the image to recognize. While in the NN method, any type of image can be useful without the requirement to particular data about the type of image, and simultaneously provides superior accuracy. In this paper, HFR system based on neural-fuzzy (NF) has been introduced. In the

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Montano Herrera, Liliana, Tobias Eilert, I.-Ting Ho, et al. "Holistic Process Models: A Bayesian Predictive Ensemble Method for Single and Coupled Unit Operation Models." Processes 10, no. 4 (2022): 662. http://dx.doi.org/10.3390/pr10040662.

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The coupling of individual models in terms of end-to-end calculations for unit operations in manufacturing processes is a challenging task. We present a probability distribution-based approach for the combined outcomes of parametric and non-parametric models. With this so-called Bayesian predictive ensemble, the statistical moments such as mean value and standard deviation can be accurately computed without any further approximation. It is shown that the ensemble of different model predictions leads to an uninformed prior distribution, which can be transformed into a predictive posterior distr

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Andersen, Torben G. "SIMULATION-BASED ECONOMETRIC METHODS." Econometric Theory 16, no. 1 (2000): 131–38. http://dx.doi.org/10.1017/s0266466600001080.

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The accessibility of high-performance computing power has always influenced theoretical and applied econometrics. Gouriéroux and Monfort begin their recent offering, Simulation-Based Econometric Methods, with a stylized three-stage classification of the history of statistical econometrics. In the first stage, lasting through the 1960's, models and estimation methods were designed to produce closed-form expressions for the estimators. This spurred thorough investigation of the standard linear model, linear simultaneous equations with the associated instrumental variable techniques, and maximum

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Baghdadi, Abtin, and Harald Kloft. "Machine-Learning-Driven Approaches for Assessment, Delegation, and Optimization of Multi-Floor Building." Buildings 15, no. 9 (2025): 1565. https://doi.org/10.3390/buildings15091565.

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This study presents a novel integrated framework for the structural analysis and optimization of multi-floor buildings by combining validated theoretical models with machine learning and evolutionary algorithms. The proposed Process–Action–Response System (PARS-Solution) accurately computes key structural responses—such as deformations, shear forces, and bending moments—based on eleven critical design parameters (P1 to P11). The significance of this research lies in its ability to automate and accelerate complex structural analysis using Adaptive Neuro-Fuzzy Inference Systems (ANFISs), achievi

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Speranskiy, Dmitriy V. "Synthesis of detection tests for fuzzy automata with finite memory." Vestnik Tomskogo gosudarstvennogo universiteta. Upravlenie, vychislitel'naya tekhnika i informatika, no. 66 (2024): 120–27. http://dx.doi.org/10.17223/19988605/66/12.

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The problem of test synthesis for fuzzy automata with finite memory is considered. The paper is based on the results obtained by the author earlier. They study linear automata (LA), a subclass of which are automata with finite memory (AFM). Both types of automata are used as models in diagnostics of discrete devices and in other applications. The advantages of LA are simplicity of realization and availability of developed mathematical apparatus for their study. AFMs allow describing the dependencies between inputs and outputs in the past and present moments of time without using states of the

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Chernozhukov, Victor, Denis Chetverikov, and Kengo Kato. "Inference on Causal and Structural Parameters using Many Moment Inequalities." Review of Economic Studies 86, no. 5 (2018): 1867–900. http://dx.doi.org/10.1093/restud/rdy065.

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Abstract This article considers the problem of testing many moment inequalities where the number of moment inequalities, denoted by $p$, is possibly much larger than the sample size $n$. There is a variety of economic applications where solving this problem allows to carry out inference on causal and structural parameters; a notable example is the market structure model of Ciliberto and Tamer (2009) where $p=2^{m+1}$ with $m$ being the number of firms that could possibly enter the market. We consider the test statistic given by the maximum of $p$ Studentized (or $t$-type) inequality-specific s

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Andrews, Donald W. K., and Patrik Guggenberger. "VALIDITY OF SUBSAMPLING AND “PLUG-IN ASYMPTOTIC” INFERENCE FOR PARAMETERS DEFINED BY MOMENT INEQUALITIES." Econometric Theory 25, no. 3 (2009): 669–709. http://dx.doi.org/10.1017/s0266466608090257.

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This paper considers inference for parameters defined by moment inequalities and equalities. The parameters need not be identified. For a specified class of test statistics, this paper establishes the uniform asymptotic validity of subsampling,mout ofnbootstrap, and “plug-in asymptotic” tests and confidence intervals for such parameters. Establishing uniform asymptotic validity is crucial in moment inequality problems because the pointwise asymptotic distributions of the test statistics of interest have discontinuities as functions of the true distribution that generates the observations.The s

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Matsushita, Yukitoshi, and Taisuke Otsu. "LIKELIHOOD INFERENCE ON SEMIPARAMETRIC MODELS WITH GENERATED REGRESSORS." Econometric Theory 36, no. 4 (2019): 626–57. http://dx.doi.org/10.1017/s026646661900029x.

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Hahn and Ridder (2013, Econometrica 81, 315–340) formulated influence functions of semiparametric three-step estimators where generated regressors are computed in the first step. This class of estimators covers several important examples for empirical analysis, such as production function estimators by Olley and Pakes (1996, Econometrica 64, 1263–1297) and propensity score matching estimators for treatment effects by Heckman, Ichimura, and Todd (1998, Review of Economic Studies 65, 261–294). The present article studies a nonparametric likelihood-based inference method for the parameters in suc

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Adams, Kelsey L., and Philip M. Grove. "The Effect of Transient Location on the Resolution of Bistable Visual and Audiovisual Motion Sequences." Perception 47, no. 9 (2018): 927–42. http://dx.doi.org/10.1177/0301006618788796.

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We examined the attention and inference accounts of audiovisual perception using the stream/bounce display, a visual stimulus wherein two identical objects move toward each other, completely superimpose, then move apart. This display has two candidate percepts: stream past each other or bounce off each other. Presented without additional visual or auditory transients, the motion sequence tends to yield the streaming percept, but when coupled with a tone or flash at the point of coincidence, the response bias flips toward bouncing. We explored two competing accounts of this effect: the attentio

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Jepriani, Sujiati, Ibayasid ., Aji Prasetya Wibawa, and Leonel Hernandez. "Deflection prediction of cantilever concrete beam using adaptive fuzzy inference system." International Journal of Engineering & Technology 7, no. 2.2 (2018): 108. http://dx.doi.org/10.14419/ijet.v7i2.2.12746.

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The cantilever concrete beam is a beam made of concrete that is only supported or clamped at one end and the other end free or without the pedestal. The measure to which a structural member gets deviated from the initial position is called deflection. All the internal forces of cantilever beam serve to hold all the external forces due to the load so that the structure remains balanced. While the beam gets deflected under the loads, bending occurs in the same plane due to which stresses are developed. From the moment balance formula after integrated and solved with required boundary conditions,

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Grassi, Simone, Mònica Coll Vidal, Oscar Campuzano, et al. "Sudden Death without a Clear Cause after Comprehensive Investigation: An Example of Forensic Approach to Atypical/Uncertain Findings." Diagnostics 11, no. 5 (2021): 886. http://dx.doi.org/10.3390/diagnostics11050886.

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Sudden death (SD) is defined as the unexpected natural death occurred within an hour after the onset of symptoms or from the last moment the subject has been seen in a healthy condition. Brugada syndrome (BrS) is one of the most remarkable cardiac causes of SD among young people. We report the case of a 20-year-old man who suddenly died after reportedly having smoked cannabis. Autopsy, toxicology, and genetic testing were performed. Autopsy found a long and thick myocardial bridging (MB) at 2 cm from the beginning of the left anterior descending coronary artery. Furthermore, at the histopathol

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Kwasniok, Frank. "Semiparametric maximum likelihood probability density estimation." PLOS ONE 16, no. 11 (2021): e0259111. http://dx.doi.org/10.1371/journal.pone.0259111.

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A comprehensive methodology for semiparametric probability density estimation is introduced and explored. The probability density is modelled by sequences of mostly regular or steep exponential families generated by flexible sets of basis functions, possibly including boundary terms. Parameters are estimated by global maximum likelihood without any roughness penalty. A statistically orthogonal formulation of the inference problem and a numerically stable and fast convex optimization algorithm for its solution are presented. Automatic model selection over the type and number of basis functions

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Raju, Kola Narasimha, Aswadhati Sirisha, Uppe Nanaji, S. K. Sharma, and Chatikam Raj Kumar. "An adaptive hello interval for AODV through ANFIS to improve the performance of MANETs." International Journal of Knowledge-based and Intelligent Engineering Systems 25, no. 2 (2021): 235–42. http://dx.doi.org/10.3233/kes-210067.

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Mobile Ad Hoc Network is an easily deployable wireless network without any need of centralized infrastructure. The change of position by wireless devicesleadstolinkfailuresandroutefailures.The mobile nodes sent hello messages at regular intervals to update the status of their neighbors. Increasing the number of periodical notifications such as hello messages will give an idea about the topology and at the same moment consumes more network resources. Reducing these periodic notifications results in discovering the neighbors at veryslowrate.Thereforetherateofhellomessages has most significant ro

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Masuta, Hiroyuki, Tatsuo Motoyoshi, Kei Sawai, Ken'ichi Koyanagi, Toru Oshima, and Hun-Ok Lim. "Direct Perception and Action Decision for Unknown Object Grasping." International Journal of Artificial Life Research 7, no. 1 (2017): 38–51. http://dx.doi.org/10.4018/ijalr.2017010103.

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This paper discusses the direct perception of an unknown object and the action decision to grasp an unknown object using depth sensor for social robots. Conventional methods estimate the accurate physical parameters when a robot wants to grasp an unknown object. Therefore, we propose a perceptual system based on an invariant concept in ecological psychology, which perceives the information relevant to the action of the robot. Firstly, we proposed the plane detection based approach for perceiving an unknown object. In this paper, we propose the sensation of grasping which is expressed by using

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Lai, Chia-Hung, Sih-Hao Huang, Ting-En Wu, and Chia-Chun Lai. "A Study on Tool Breakage Detection Technology Based on Current Sensing and Non-Contact Signal Analysis." Sensors 25, no. 13 (2025): 3880. https://doi.org/10.3390/s25133880.

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Tool breakage in CNC machining often leads to reduced productivity and increased maintenance costs. This study proposes a non-contact tool breakage detection method using spindle current signals captured by an SCT013 current sensor. The sensor easily attaches to the motor line without any hardware modification and provides real-time current signals for frequency domain analysis. Fast Fourier Transform (FFT) is employed to extract spectral features, particularly focusing on high-frequency energy spikes at the moment of breakage. A total of 20 experiments were conducted, and consistent spectral

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Magdalinos, Tassos, and Peter C. B. Phillips. "LIMIT THEORY FOR COINTEGRATED SYSTEMS WITH MODERATELY INTEGRATED AND MODERATELY EXPLOSIVE REGRESSORS." Econometric Theory 25, no. 2 (2009): 482–526. http://dx.doi.org/10.1017/s0266466608090154.

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An asymptotic theory is developed for multivariate regression in cointegrated systems whose variables are moderately integrated or moderately explosive in the sense that they have autoregressive roots of the form ρni = 1 + ci/nα, involving moderate deviations from unity when α ∈ (0, 1) and ci ∈ ℝ are constant parameters. When the data are moderately integrated in the stationary direction (with ci < 0), it is shown that least squares regression is consistent and asymptotically normal but suffers from significant bias, related to simultaneous equations bias. In the moderately explosive case (

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Teunissen, W., S. Derks, J. Labrecque, et al. "P11.06.B PERFUSION MRI IMPACTS MANAGEMENT IN PATIENTS WITH TREATED GLIOMA: FIRST RESULTS FROM THE PERISCOPE PROJECT." Neuro-Oncology 25, Supplement_2 (2023): ii73. http://dx.doi.org/10.1093/neuonc/noad137.240.

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Abstract BACKGROUND Perfusion MRI (pMRI) is widely used for differentiation between progressive disease and pseudoprogression in patients with treated glioma. Although pMRI has long been available, its clinical relevance and utilization are not well known. We investigate the role of pMRI in clinical management decisions and its association with overall survival (OS) in patients with glioma under surveillance after focal radiotherapy. MATERIALS AND METHODS We performed a retrospective multicenter cohort study of patients treated for glioma between 2008 and 2021. At the moment of first substanti

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Yu, Zhiyuan, Wenzhong Li, Zhangyue Yin, Xiaobin Hong, Shijian Xiao, and Sanglu Lu. "Contextual Structure Knowledge Transfer for Graph Neural Networks." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 21 (2025): 22263–71. https://doi.org/10.1609/aaai.v39i21.34381.

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Graph transfer learning endeavors to develop a Graph Neural Network (GNN) model in a fully-labeled source domain, with the intention of deploying it on a target domain that has limited labeled data for inference. We reveal that prevalent graph transfer learning methods are susceptible to the homophily shift problem. This issue arises from the divergence in homophily structures between the source and target graphs, leading to a notable deterioration in the performance of GNN models. In this paper, we introduce a novel Contextual Structural Graph Neural Network (CS-GNN) method, leveraging a tail

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Lambon, Justice Iddrisu, Evans O. N. D. Ocansey, and Opoku Kwaku Ababio. "Influence of employment on economic growth in Sub-Saharan Africa. Does financial stability matter?" International Journal of Finance 10, no. 5 (2025): 34–51. https://doi.org/10.47941/ijf.2880.

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Purpose: The primary objective is to determine whether employment significantly influences economic growth and how financial stability, alongside other macroeconomic variables, affects this relationship. Methodology: To achieve this, the study employs a robust quantitative design using panel data from 38 SSA countries covering the period from 2000 to 2023. The analysis utilizes the Generalized Method of Moments (GMM) technique, which controls for endogeneity, unobserved heterogeneity, and autocorrelation, ensuring the credibility of causal inferences. Findings: Empirical results reveal that em

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Bao, Peijun, Yong Xia, Wenhan Yang, Boon Poh Ng, Meng Hwa Er, and Alex C. Kot. "Local-Global Multi-Modal Distillation for Weakly-Supervised Temporal Video Grounding." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 2 (2024): 738–46. http://dx.doi.org/10.1609/aaai.v38i2.27831.

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This paper for the first time leverages multi-modal videos for weakly-supervised temporal video grounding. As labeling the video moment is labor-intensive and subjective, the weakly-supervised approaches have gained increasing attention in recent years. However, these approaches could inherently compromise performance due to inadequate supervision. Therefore, to tackle this challenge, we for the first time pay attention to exploiting complementary information extracted from multi-modal videos (e.g., RGB frames, optical flows), where richer supervision is naturally introduced in the weaklysuper

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Liu, Gang, Silu He, Xing Han, et al. "Self-Supervised Spatiotemporal Masking Strategy-Based Models for Traffic Flow Forecasting." Symmetry 15, no. 11 (2023): 2002. http://dx.doi.org/10.3390/sym15112002.

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Traffic flow forecasting is an important function of intelligent transportation systems. With the rise of deep learning, building traffic flow prediction models based on deep neural networks has become a current research hotspot. Most of the current traffic flow prediction methods are designed from the perspective of model architectures, using only the traffic features of future moments as supervision signals to guide the models to learn the spatiotemporal dependence in traffic flow. However, traffic flow data themselves contain rich spatiotemporal features, and it is feasible to obtain additi

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Louviot, Elise. "Semantic bleaching of nu in Old Saxon." Folia Linguistica 39, no. 2 (2018): 441–73. http://dx.doi.org/10.1515/flih-2018-0016.

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Abstract In many Present-Day Germanic languages, reflexes of Proto-Germanic *nu have developed pragmatic and grammatical uses: in such uses, the earlier, lexical meaning of the word (“now”, “presently”) has been weakened or lost while new meanings have appeared. Pragmatic (especially connective) uses of nu have been identified in several ancient Germanic languages, but in such corpora, it can be difficult to distinguish between a genuine discourse marker and mere pragmatic inferences based on the lexical meaning of a given word. Such is certainly the case for Old Saxon, where nu seems to be us

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Dingeto, Hiskias, and Juntae Kim. "Comparative Study of Adversarial Defenses: Adversarial Training and Regularization in Vision Transformers and CNNs." Electronics 13, no. 13 (2024): 2534. http://dx.doi.org/10.3390/electronics13132534.

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Transformer-based models are driving a significant revolution in the field of machine learning at the moment. Among these innovations, vision transformers (ViTs) stand out for their application of transformer architectures to vision-related tasks. By demonstrating performance as good, if not better, than traditional convolutional neural networks (CNNs), ViTs have managed to capture considerable interest in the field. This study focuses on the resilience of ViTs and CNNs in the face of adversarial attacks. Such attacks, which introduce noise into the input of machine learning models to produce

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ÖREN, Ezgi. "Ütopya Şimdi ve Daima: Ütopyanın Daimiliği Üzerine Bir Tartışma." İnsan ve Toplum Bilimleri Araştırmaları Dergisi 12, no. 3 (2023): 2279–89. http://dx.doi.org/10.15869/itobiad.1320471.

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The history of humanity is, in a way, the history of the chaos that is immanent in society. People have endless desires that could never be satisfied since they lived in society. The demand for a better life is one of the foremost desires. This quest, which has been lasting since the beginning of social life has been tried to be met with a wide variety of solutions throughout history. Perhaps the most striking of these propositions is Utopia, which took the stage with the Renaissance. It emphasizes the reality of the moment, criticizes it, and replaces it with an alternative that never comes t

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Fedorov, Kirill. "Integrating the predictive processing and the cognitive dissonance theories in the context of rational choice problem." Philosophy Journal 17, no. 1 (2024): 180–96. http://dx.doi.org/10.21146/2072-0726-2024-17-1-180-196.

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A significant problem in constructing the theory of rational choice (and rationality in general) at the moment is the question of explaining irrationality, or rather the fact that an agent can act irrationally for an external observer, and the models used for it may not work. However, the agent himself “inside”, if you find yourself in his “logic”, acts clearly rationally upon verification. It’s just that his “rationality” and the “rationality” of an external observer turn out to be different, hence they do not coincide, and hence this leads to a discrepancy in the language of their descript

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Deshmukh, Jay. "Speculations on the post-pandemic university campus – a global inquiry." Archnet-IJAR: International Journal of Architectural Research 15, no. 1 (2021): 131–47. http://dx.doi.org/10.1108/arch-10-2020-0245.

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PurposeThe pandemic-induced global shift to remote learning calls for rethinking the foundations of design for higher education. This watershed moment in global health and human interaction has accelerated changes in higher education that were long emergent and amplified specific deficiencies and strengths in pedagogical models, causing institutions to reevaluate current structures and operations of learning and campus life as they question their vision and purpose. Since physical space has largely been taken out of the equation of university life, it is evident that fresh design research rela

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Magno Lopes, José Manuel, and Florencio Vicente Castro. "CONTRATO PSICOLÓGICO: FORMALIZAÇÃO DA LINGUAGEM." International Journal of Developmental and Educational Psychology. Revista INFAD de Psicología. 3, no. 1 (2017): 367. http://dx.doi.org/10.17060/ijodaep.2017.n1.v3.1004.

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Abstract.PSYCHOLOGICAL CONTRACT: FORMALIZATION OF LANGUAGEConceptual Framework: A fundamental aspect in the study of the psychological contract it to provide a broad model of analysis, by understanding the individual’s perceptions, emotions and behaviour, as well as the moment and context in which they occur with the aim of intervening in relationships that promote a major commitment between the parties.Objectives: The current literature, in particular authors such as Rousseau and Guest, presents some models of psychological contract which are applicable in specific contexts as well as methodo

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Schertzer, D., and E. Falgarone. "MFGA-IDT2 workshop: Astrophysical and geophysical fluid mechanics: the impact of data on turbulence theories." Nonlinear Processes in Geophysics 3, no. 4 (1996): 229–30. http://dx.doi.org/10.5194/npg-3-229-1996.

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Abstract. 1 Facts about the Workshop This workshop was convened on November 13-15 1995 by E. Falgarone and D. Schertzer within the framework of the Groupe de Recherche Mecanique des Fluides Geophysiques et Astrophysiques (GdR MFGA, Research Group of Geophysical and Astrophysical Fluid Mechanics) of Centre National de la Recherche Scientifique (CNRS, (French) National Center for Scientific Research). This Research Group is chaired by A. Babiano and the meeting was held at Ecole Normale Superieure, Paris, by courtesy of its Director E. Guyon. More than sixty attendees participated to this worksh

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Kim, Hara. "The Meeting of Historical Geography and Classical Literature Education -Focusing on the Exploration of Place in Playing Jeopo at Manboksa Temple-." Society Of Korean Literature 48 (November 30, 2023): 43–82. http://dx.doi.org/10.52723/jkl.48.043.

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In this paper, I attempted to explore the historical and geographical specificity of the space represented in Kim Si-seup’s novel Playing Jeopo at Manboksa Temple. The spatial setting of this novel is Namwon-si, Jeollabuk-do. Kim Si-seup actually traveled to Honam in 1462 when he was 28 years old and reflected his experience of exploring the Namwon area, including Manboksa Temple, in the creation of the novel space. Therefore, the place names mentioned in this novel serve as an important clue to the historical and geographical approach as actual places in Namwon town. The work of specifically

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Francq, Christian, Baye Matar Kandji, and Jean-Michel Zakoian. "INFERENCE ON GARCH-MIDAS MODELS WITHOUT ANY SMALL-ORDER MOMENT." Econometric Theory, May 12, 2023, 1–34. http://dx.doi.org/10.1017/s0266466623000142.

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In GARCH-mixed-data sampling models, the volatility is decomposed into the product of two factors which are often interpreted as “short-run” (high-frequency) and “long-run” (low-frequency) components. While two-component volatility models are widely used in applied works, some of their theoretical properties remain unexplored. We show that the strictly stationary solutions of such models do not admit any small-order finite moment, contrary to classical GARCH. It is shown that the strong consistency and the asymptotic normality of the quasi-maximum likelihood estimator hold despite the absence

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Öztürk, Büruce, Elif Kemah, Hakan Yakut, Emre Tabar, and Gamze Hoşgör. "Inference and Visualization of Nuclear Magnetic Moment Studies with Neuro-Fuzzy Systems." Physica Scripta, August 14, 2023. http://dx.doi.org/10.1088/1402-4896/acf004.

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Abstract This study aims to predict the magnetic moments of nuclei with odd-A numbers in a certain region of which magnetic moment has not yet been calculated, using the Adaptive Neuro-Fuzzy Inference System (Anfis) method. In our Anfis model, the proton number (Z), neutron number (N), and spin value (I) are used as inputs for nuclei with 1≤Z≤88. With these input data, 526 odd-A nuclei are trained, and 124 nuclei are tested. The fact that the Anfis model was closer to the experimental data in the training and testing processes than the theoretical methods encouraged us to make inferences about

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Poskitt, Donald S. "ON GMM INFERENCE: PARTIAL IDENTIFICATION, IDENTIFICATION STRENGTH, AND NONSTANDARD ASYMPTOTICS." Econometric Theory, September 18, 2023, 1–51. http://dx.doi.org/10.1017/s0266466623000221.

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This paper analyses aspects of generalized method of moments (GMM) inference in moment equality models in settings where standard regularity conditions may break down. Explicit analytic formulations for the asymptotic distributions of estimable functions of the GMM estimator and statistics based on the GMM criterion function are derived under relatively mild assumptions. The moment Jacobian is allowed to be rank deficient, so first order identification may fail, the values of the Jacobian singular values are not constrained, thereby allowing for varying levels of identification strength, the l

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Katsumata, Hiroto. "How should we estimate inverse probability weights with possibly misspecified propensity score models?" Political Science Research and Methods, August 15, 2024, 1–22. http://dx.doi.org/10.1017/psrm.2024.23.

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Abstract Inverse probability weighting is a common remedy for missing data issues, notably in causal inference. Despite its prevalence, practical application is prone to bias from propensity score model misspecification. Recently proposed methods try to rectify this by balancing some moments of covariates between the target and weighted groups. Yet, bias persists without knowledge of the true outcome model. Drawing inspiration from the quasi maximum likelihood estimation with misspecified statistical models, I propose an estimation method minimizing a distance between true and estimated weight

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Chiang, Harold D., Jiatong Li, and Yuya Sasaki. "ALGORITHMIC SUBSAMPLING UNDER MULTIWAY CLUSTERING." Econometric Theory, July 11, 2023, 1–44. http://dx.doi.org/10.1017/s0266466623000166.

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This paper proposes a novel method of algorithmic subsampling (data sketching) for multiway cluster-dependent data. We establish a new uniform weak law of large numbers and a new central limit theorem for multiway algorithmic subsample means. We show that algorithmic subsampling allows for robustness against potential degeneracy, and even non-Gaussian degeneracy, of the asymptotic distribution under multiway clustering at the cost of efficiency and power loss due to algorithmic subsampling. Simulation studies support this novel result, and demonstrate that inference with algorithmic subsamplin

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Shams, Mehdi, and Mohammad Ali Mirzaie. "Statistical Inference and Simulation for the Maxwell‐Boltzmann Distribution." Advanced Theory and Simulations, May 7, 2025. https://doi.org/10.1002/adts.202500148.

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AbstractStatistical simulation is one approach to problem solving without experimental testing. In this paper, a method for simulating the distribution of the Maxwell‐Boltzmann distribution with MCMC approach by truncated Rayleigh distribution is presented and generated a random sample from this distribution by rejection sampling method. Some statistical inference properties for the parameter of the Maxwell‐Boltzmann distribution such as maximum likelihood estimator, method of moments estimator, uniformly minimum variance unbiased estimator and minimum risk equivariant estimator, and the relat

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Richards, Kylie-Anne, William T. M. Dunsmuir, and Gareth W. Peters. "Score test for marks in Hawkes processes." International Journal of Data Science and Analytics, October 10, 2024. http://dx.doi.org/10.1007/s41060-024-00644-4.

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AbstractA score statistic for detecting the impact of marks in a linear Hawkes self-exciting point process is proposed, with its asymptotic properties, finite sample performance, power properties using simulation and application to real data presented. A major advantage of the proposed inference procedure is that the Hawkes process can be fitted under the null hypothesis that marks do not impact the intensity process. Hence, for a given record of a point process, the intensity process is estimated once only and then assessed against any number of potential marks without refitting the joint lik

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Lewis, Daniel J. "Identifying Shocks via Time-Varying Volatility." Review of Economic Studies, May 17, 2021. http://dx.doi.org/10.1093/restud/rdab009.

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Abstract I propose to identify an SVAR, up to shock ordering, using the autocovariance structure of the squared innovations implied by an arbitrary stochastic process for the shock variances. These higher moments are available without parametric assumptions on the variance process. In contrast, previous approaches exploiting heteroskedasticity rely on the path of innovation covariances, which can only be recovered from the data under specific parametric assumptions on the variance process. The conditions for identification are testable. I compare the identification scheme to existing approache

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Palmero, Francisco, Trevor J. Hefley, Josefina Lacasa, et al. "A Bayesian approach for estimating the uncertainty on the contribution of nitrogen fixation and calculation of nutrient balances in grain legumes." Plant Methods 20, no. 1 (2024). http://dx.doi.org/10.1186/s13007-024-01261-9.

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Abstract Background The proportion of nitrogen (N) derived from the atmosphere (Ndfa) is a fundamental component of the plant N demand in legume species. To estimate the N benefit of grain legumes for the subsequent crop in the rotation, a simplified N balance is frequently used. This balance is calculated as the difference between fixed N and removed N by grains. The Ndfa needed to achieve a neutral N balance (hereafter $$\theta$$ θ ) is usually estimated through a simple linear regression model between Ndfa and N balance. This quantity is routinely estimated without accounting for the uncert

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Rajpold, Wojciech. "The use of statistical models to determine the age of the deceased and the issue of children’s graves identified by the models as adult burials. Based on the example of burials of Tarnobrzeg Lusatian Culture." Praehistorische Zeitschrift, March 31, 2022. http://dx.doi.org/10.1515/pz-2022-2042.

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Abstract Childhood is the moment in every man’s life when they learn the rules governing the society to which they belong. This process of learning certain principles usually ends when the individual reaches the appropriate age. In primitive communities it was necessary to undergo complex and sometimes painful initiation processes. These moments could be different from one another depending on the community and gender, and what is more, it was often multi-stage. It usually occurred at the age of 14/15 for boys and even a little earlier for girls. It is assumed that up to 60 % of people in the

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Chen, Xiaohong, Lars Peter Hansen, and Peter Hansen. "Robust Inference for Moment Condition Models without Rational Expectations." SSRN Electronic Journal, 2021. http://dx.doi.org/10.2139/ssrn.3945856.

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Chen, Xiaohong, Lars Peter Hansen, and Peter G. Hansen. "Robust inference for moment condition models without rational expectations." Journal of Econometrics, January 2024, 105653. http://dx.doi.org/10.1016/j.jeconom.2023.105653.

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Nguyen, Long H. B., Nghi T. Pham, Le D. C. Duc, Cong Duy Vu Hoang, and Dien Dinh. "Moment matching training for neural machine translation: An empirical study." Journal of Intelligent & Fuzzy Systems, March 17, 2022, 1–13. http://dx.doi.org/10.3233/jifs-213240.

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In recent years, Neural Machine Translation (NMT), which harnesses the power of neural networks, has achieved astonishing achievements. Despite its promise, NMT models can still not model prior external knowledge. Recent investigations have necessitated the adaptation of past expertise to both training and inference methods, resulting in translation inference issues. This paper proposes an extension of the moment matching framework that incorporates advanced prior knowledge without interfering with the inference process by using a matching mechanism between the model and empirical distribution

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Chen, Xiaohong, Sokbae Lee, Myung Hwan Seo, and Myunghyun Song. "Inference for Parameters Identified by Conditional Moment Restrictions Using a Generalized Bierens Maximum Statistic." Review of Economics and Statistics, January 28, 2025, 1–45. https://doi.org/10.1162/rest_a_01550.

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Abstract Many economic panel and dynamic models, such as rational behavior and Euler equations, imply that the parameters of interest are identified by conditional moment restrictions. We introduce a novel inference method without any prior information about which conditioning instruments are weak or irrelevant. Building on Bierens (1990), we propose penalized maximum statistics and combine bootstrap inference with model selection. Our method optimizes asymptotic power by solving a data-dependent max-min problem for tuning parameter selection. Extensive Monte Carlo experiments, based on an emp

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Saoulis, A. A., D. Piras, A. Spurio Mancini, B. Joachimi, and A. M. G. Ferreira. "Full-waveform earthquake source inversion using simulation-based inference." Geophysical Journal International, March 28, 2025. https://doi.org/10.1093/gji/ggaf112.

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Summary This paper presents a novel framework for full-waveform seismic source inversion using simulation-based inference (SBI). Traditional probabilistic approaches often rely on simplifying assumptions about data errors, which we show can lead to inaccurate uncertainty quantification. SBI addresses this limitation by learning an empirical probabilistic relationship between the parameters and data, without making assumptions about the data errors. This is achieved through the use of specialised machine learning models, known as neural density estimators, which can then be integrated into the

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Bonofiglio, Federico. "Survival Analysis Without Sharing of Individual Patient Data by Using a Gaussian Copula." Pharmaceutical Statistics, July 7, 2024. http://dx.doi.org/10.1002/pst.2415.

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ABSTRACTCox regression and Kaplan–Meier estimations are often needed in clinical research and this requires access to individual patient data (IPD). However, IPD cannot always be shared because of privacy or proprietary restrictions, which complicates the making of such estimations. We propose a method that generates pseudodata replacing the IPD by only sharing non‐disclosive aggregates such as IPD marginal moments and a correlation matrix. Such aggregates are collected by a central computer and input as parameters to a Gaussian copula (GC) that generates the pseudodata. Survival inferences ar

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Arvanitis, Stelios, and Antonis Demos. "On the Validity of Edgeworth Expansions and Moment Approximations for Three Indirect Inference Estimators." Journal of Econometric Methods 7, no. 1 (2016). http://dx.doi.org/10.1515/jem-2015-0009.

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AbstractThis paper deals with higher order asymptotic properties for three indirect inference estimators. We provide conditions that ensure the validity of locally uniform, with respect to the parameter, Edgeworth approximations. When these are of sufficiently high order they also form integrability conditions that validate locally uniform moment approximations. We derive the relevant second order bias and MSE approximations for the three estimators as functions of the respective approximations for the auxiliary estimator. We confirm that in the special case of deterministic weighting and affi

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