Relevant bibliographies by topics / Gradient implicite

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Gradient implicite'

Author: Grafiati
Published: 31 August 2024
Last updated: 19 July 2025

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Journal articles on the topic "Gradient implicite"

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Weller, Hilary, and Ava Shahrokhi. "Curl-Free Pressure Gradients over Orography in a Solution of the Fully Compressible Euler Equations with Implicit Treatment of Acoustic and Gravity Waves." Monthly Weather Review 142, no. 12 (2014): 4439–57. http://dx.doi.org/10.1175/mwr-d-14-00054.1.

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Abstract Steep orography can cause noisy solutions and instability in models of the atmosphere. A new technique for modeling flow over orography is introduced that guarantees curl-free gradients on arbitrary grids, implying that the pressure gradient term is not a spurious source of vorticity. This mimetic property leads to better hydrostatic balance and better energy conservation on test cases using terrain-following grids. Curl-free gradients are achieved by using the covariant components of velocity over orography rather than the usual horizontal and vertical components. In addition, gravit
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Askes, Harm, and Miguel A. Gutiérrez. "Implicit gradient elasticity." International Journal for Numerical Methods in Engineering 67, no. 3 (2006): 400–416. http://dx.doi.org/10.1002/nme.1640.

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Haugh, Jason M., Franca Codazzi, Mary Teruel, and Tobias Meyer. "Spatial Sensing in Fibroblasts Mediated by 3′ Phosphoinositides." Journal of Cell Biology 151, no. 6 (2000): 1269–80. http://dx.doi.org/10.1083/jcb.151.6.1269.

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The directed movement of fibroblasts towards locally released platelet-derived growth factor (PDGF) is a critical event in wound healing. Although recent studies have implicated polarized activation of phosphoinositide (PI) 3-kinase in G protein-mediated chemotaxis, the role of 3′ PI lipids in tyrosine kinase-triggered chemotaxis is not well understood. Using evanescent wave microscopy and green fluorescent protein–tagged Akt pleckstrin homology domain (GFP–AktPH) as a molecular sensor, we show that application of a shallow PDGF gradient triggers a markedly steeper gradient in 3′ PI lipids in
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Minervini, Pasquale, Luca Franceschi, and Mathias Niepert. "Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 8 (2023): 9200–9208. http://dx.doi.org/10.1609/aaai.v37i8.26103.

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The integration of discrete algorithmic components in deep learning architectures has numerous applications. Recently, Implicit Maximum Likelihood Estimation, a class of gradient estimators for discrete exponential family distributions, was proposed by combining implicit differentiation through perturbation with the path-wise gradient estimator. However, due to the finite difference approximation of the gradients, it is especially sensitive to the choice of the finite difference step size, which needs to be specified by the user. In this work, we present Adaptive IMLE (AIMLE), the first adapti
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Dong, Mingrong, Yixuan Yang, Kai Zeng, Qingwang Wang, and Tao Shen. "Implicit Sharpness-Aware Minimization for Domain Generalization." Remote Sensing 16, no. 16 (2024): 2877. http://dx.doi.org/10.3390/rs16162877.

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Domain generalization (DG) aims to learn knowledge from multiple related domains to achieve a robust generalization performance in unseen target domains, which is an effective approach to mitigate domain shift in remote sensing image classification. Although the sharpness-aware minimization (SAM) method enhances DG capability and improves remote sensing image classification performance by promoting the convergence of the loss minimum to a flatter loss surface, the perturbation loss (maximum loss within the neighborhood of a local minimum) of SAM fails to accurately measure the true sharpness o
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Bertei, Antonio, Andrea Lamorgese, and Roberto Mauri. "Constitutive Relations of Thermal and Mass Diffusion." Journal of Non-Equilibrium Thermodynamics 45, no. 1 (2020): 27–38. http://dx.doi.org/10.1515/jnet-2019-0055.

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AbstractNon-equilibrium thermodynamics provides a general framework for the description of mass and thermal diffusion, thereby including also cross-thermal and material diffusion effects, which are generally modeled through the Onsager coupling terms within the constitutive equations relating heat and mass flux to the gradients of temperature and chemical potential. These so-called Soret and Dufour coefficients are not uniquely defined, though, as they can be derived by adopting one of the several constitutive relations satisfying the principles of non-equilibrium thermodynamics. Therefore, ma
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Nishikawa, Hiroaki. "From hyperbolic diffusion scheme to gradient method: Implicit Green–Gauss gradients for unstructured grids." Journal of Computational Physics 372 (November 2018): 126–60. http://dx.doi.org/10.1016/j.jcp.2018.06.019.

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Gourmel, Olivier, Loic Barthe, Marie-Paule Cani, et al. "A gradient-based implicit blend." ACM Transactions on Graphics 32, no. 2 (2013): 1–12. http://dx.doi.org/10.1145/2451236.2451238.

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Dandi, Yatin, Luis Barba, and Martin Jaggi. "Implicit Gradient Alignment in Distributed and Federated Learning." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 6 (2022): 6454–62. http://dx.doi.org/10.1609/aaai.v36i6.20597.

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A major obstacle to achieving global convergence in distributed and federated learning is the misalignment of gradients across clients or mini-batches due to heterogeneity and stochasticity of the distributed data. In this work, we show that data heterogeneity can in fact be exploited to improve generalization performance through implicit regularization. One way to alleviate the effects of heterogeneity is to encourage the alignment of gradients across different clients throughout training. Our analysis reveals that this goal can be accomplished by utilizing the right optimization method that
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Nelson, J. Bradley. "An alternate derivation of the three‐dimensional Hilbert transform relations from first principles." GEOPHYSICS 51, no. 4 (1986): 1014–15. http://dx.doi.org/10.1190/1.1442141.

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Several techniques for determining the location, geometry, and strength of a source are based on a knowledge of the magnetic gradients generated by that source. Hood (1965), Bhattacharyya (1966), and Rao et al. (1981) detailed three of these gradient methods. For many years, geophysicists have used the two‐dimensional (2-D) Hilbert transform to approximate the vertical gradient from measurements of the horizontal gradient in the magnetic‐field intensity (Nabighian, 1972; Stanley and Green, 1976; Stanley, 1977; Mohan et al., 1982). This technique is of limited applicability because of the impli
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Dissertations / Theses on the topic "Gradient implicite"

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Ribeiro, Nogueira Breno. "Non-local damage mechanics with evolving interactions for modeling quasi-brittle materials : anisotropic damage and gradient-enhanced Eikonal approach." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPAST072.

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La prévision de la nucléation et de la propagation des fissures est essentielle pour décrire la réponse des structures dans des conditions de chargement complexes. On observe l'apparition de microfissures diffuses avant la formation d'une macrofissure. Dans le cas de matériaux quasi-fragiles, on observe un comportement adoucissant lié à une perte progressive de rigidité. D'un point de vue thermodynamique, ce comportement peut être décrit de manière continue par une variable d'état d'endommagement. Cependant, les modèles d'endommagement locaux conduisent inévitablement à un problème aux valeurs
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Charlton, Timothy James. "An implicit Generalised Interpolation Material Point Method for large deformation and gradient elasto-plasticity." Thesis, Durham University, 2018. http://etheses.dur.ac.uk/12824/.

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The ability to correctly capture large deformation behaviour in solids is important in many problems in geotechnical engineering such as slope failure or installation of foundations. The Material Point Method (MPM) is a computational method with particular suitability for modelling problems involving large deformations. In the MPM, a domain is modelled using a set of material points at which state variables are stored and tracked. These material points move through a fixed background grid upon which calculations take place with variables being mapped between the material points and the grid. T
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Townshend, Julia Margaret. "A study of implicit memory and temporal gradients in retrograde amnesia and semantic dementia." Thesis, University of Sussex, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340797.

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This thesis sets out to test some of the predictions proposed by a recent connectionist model of memory and amnesia. The model proposes a time limited role for the hippocampus in memory consolidation in which memories once dependent on the hippocampus become independent of the hippocampus over time and fully supported by the neocortex. The predictions that are made by the model are that there will be memories in retrograde amnesia that are only available through implicit tests of memory; that implicit memory in retrograde amnesia will show a temporal gradient; that semantic dementia patients w
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Jackson, Sarah Marie. "The Influence of Implicit and Explicit Gender Bias on Grading, and the Effectiveness of Rubrics for Reducing Bias." Wright State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=wright1464731201.

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De, Santis Dante. "Development of a high-order residual distribution method for Navier-Stokes and RANS equations." Phd thesis, Université Sciences et Technologies - Bordeaux I, 2013. http://tel.archives-ouvertes.fr/tel-00946171.

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The construction of compact high-order Residual Distribution schemes for the discretizationof steady multidimensional advection-diffusion problems on unstructuredgrids is presented. Linear and non-linear scheme are considered. A piecewise continuouspolynomial approximation of the solution is adopted and a gradient reconstructionprocedure is used in order to have a continuous representation of both thenumerical solution and its gradient. It is shown that the gradient must be reconstructedwith the same accuracy of the solution, otherwise the formal accuracy ofthe numerical scheme is lost in appl
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Haley, James. "To Curve or Not to Curve? The Effect of College Science Grading Policies on Implicit Theories of Intelligence, Perceived Classroom Goal Structures, and Self-efficacy." Thesis, Boston College, 2015. http://hdl.handle.net/2345/bc-ir:104165.

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Thesis advisor: George M. Barnett<br>There is currently a shortage of students graduating with STEM (science, technology, engineering, or mathematics) degrees, particularly women and students of color. Approximately half of students who begin a STEM major eventually switch out. Many switchers cite the competitiveness, grading curves, and weed-out culture of introductory STEM classes as reasons for the switch. Variables known to influence resilience include a student's implicit theory of intelligence and achievement goal orientation. Incremental theory (belief that intelligence is malleable) an
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De, Santis Dante. "Schémas d'ordre élevé distribuant le résidu pour la résolution des équations de Navier-Stokes et Navier-Stokes moyennées (RANS)." Phd thesis, Université Sciences et Technologies - Bordeaux I, 2013. http://tel.archives-ouvertes.fr/tel-00935419.

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Cette thèse présente la construction de schémas distribuant le résidu (RD) d'ordre très élevés, pour la discrétisation d'équations d'advection-diffusion multidimensionnelles et stationnaires sur maillages non structurés. Des schémas linéaires ainsi que des schémas non linéaires sont considérés. Une approximation de la solution polynomiale par morceaux et continue sur chaque élément est adoptée, de plus une procédure de reconstruction du gradient que celle de la solution numérique est utilisée afin d'avoir une représentation continue de la solution numérique et de son gradient. Il est montré qu
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Cai, Shang-Gui. "Computational fluid-structure interaction with the moving immersed boundary method." Thesis, Compiègne, 2016. http://www.theses.fr/2016COMP2276/document.

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Dans cette thèse, une nouvelle méthode de frontières immergées a été développée pour la simulation d'interaction fluide-structure, appelée la méthode de frontières immergées mobiles (en langage anglo-saxon: MIBM). L'objectif principal de cette nouvelle méthode est de déplacer arbitrairement les solides à géométrie complexe dans un fluide visqueux incompressible, sans remailler le domaine fluide. Cette nouvelle méthode a l'avantage d'imposer la condition de non-glissement à l'interface d'une manière exacte via une force sans introduire des constantes artificielles modélisant la structure rigide
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Singh, Manish Kumar. "Implicit Gradient Reconstruction for Unstructured Mesh Finite Volume Method." Thesis, 2022. https://etd.iisc.ac.in/handle/2005/5934.

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In the present work, an Implicit Gradient Reconstruction (IGR) method is proposed in the context of Finite Volume Methodology (FVM). There are three computationally intensive steps involved in a typical finite volume framework for a spatially second-order accurate upwind scheme. These are solution reconstruction, solution limiting and flux finding. Solution re- construction involves determination of gradients while solution limiting requires comparison of double precision numbers. Further, computation of gradient and solution limiting is cell based procedure while flux finding is edge/fa
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CICERI, ANDREA. "Il ruolo del wine packaging nel processo decisionale: confronto tra consumatori danesi e italiani integrando metodologia tradizionale e di neuromarketing." Doctoral thesis, 2017. http://hdl.handle.net/10808/22423.

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La ricerca realizzata ha preso in esame il processo decisionale del vino, focalizzandosi in particolar modo sul ruolo che ha l’aspetto estetico del packaging. Si è deciso da un lato di prendere a oggetto di studio questo prodotto, in quanto connotato da una elevata percezione di rischio. Dall’altro, si è ristretto l’ambito decisionale al solo packaging, poiché è un elemento che assume un ruolo del tutto peculiare e fondamentale nel processo decisionale di questo prodotto. Bottiglie con soluzioni estetiche gradite hanno infatti una maggiore probabilità di essere scelte, una maggiore disponi
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Books on the topic "Gradient implicite"

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1929-, Chung T. J., and United States. National Aeronautics and Space Administration., eds. Flowfield-dependent mixed explicit-implicit (FDMEI) algorithm for computational fluid dynamics: Final report ... National Aeronautics and Space Administration, 1997.

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Baysal, Oktay. Efficient gradient-based shape optimization methodology using inviscid/viscous CFD: Summary of research report for the period of March 9, 1995 to March 8, 1997, grant# NCC-1-211. Dept. of Aerospace Engineering, College of Engineering and Technology, Old Dominion University, 1997.

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United States. National Aeronautics and Space Administration., ed. Efficient gradient-based shape optimization methodology using inviscid/viscous CFD: Summary of research report for the period of March 9, 1995 to March 8, 1997, grant# NCC-1-211. Dept. of Aerospace Engineering, College of Engineering and Technology, Old Dominion University, 1997.

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United States. National Aeronautics and Space Administration., ed. Efficient gradient-based shape optimization methodology using inviscid/viscous CFD: Summary of research report for the period of March 9, 1995 to March 8, 1997, grant# NCC-1-211. Dept. of Aerospace Engineering, College of Engineering and Technology, Old Dominion University, 1997.

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Townshend, Julia Margaret. A study of implicit memory and temporal gradients in retrograde amnesia and semantic dementia. 2001.

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Flowfield-dependent mixed explicit-implicit (FDMEI) algorithm for computational fluid dynamics: Final report ... National Aeronautics and Space Administration, 1997.

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Flowfield-dependent mixed explicit-implicit (FDMEI) algorithm for computational fluid dynamics: Final report ... National Aeronautics and Space Administration, 1997.

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Mann, Peter. Matrices. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198822370.003.0031.

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This chapter looks at the calculus of a function of two or more variables, which is the subject of partial differentiation. The partial derivative of a function is the rate of change of the function with respect to the distance in the direction of a particular coordinate axis and is symbolised with the sign ∂. The chapter spends time on the implicit function theorem, since it is relied upon heavily elsewhere in the text. Lagrange multipliers are used to solve constrained optimisation problems. Topics include critical points, the product rule, the chain rule, directional derivatives, hypersurfa
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Efficient gradient-based shape optimization methodology using inviscid/viscous CFD: Summary of research report for the period of March 9, 1995 to March 8, 1997, grant# NCC-1-211. Dept. of Aerospace Engineering, College of Engineering and Technology, Old Dominion University, 1997.

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Book chapters on the topic "Gradient implicite"

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He, Fengxiang, and Dacheng Tao. "Stochastic Gradient Descent as an Implicit Regularization." In Machine Learning: Foundations, Methodologies, and Applications. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-16-8233-9_6.

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Lyu, Yueming, and Ivor W. Tsang. "Black-Box Optimizer with Stochastic Implicit Natural Gradient." In Machine Learning and Knowledge Discovery in Databases. Research Track. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86523-8_14.

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Hillman, M., and J. S. Chen. "An Implicit Gradient Meshfree Formulation for Convection-Dominated Problems." In Advances in Computational Fluid-Structure Interaction and Flow Simulation. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40827-9_3.

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Bayer, Hakan, Benedikt Faltin, and Markus König. "Automated Extraction of Bridge Gradient from Drawings Using Deep Learning." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/979-12-215-0289-3.68.

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Digital methods such as Building Information Modeling (BIM) can be leveraged, to improve the efficiency of maintenance planning of bridges. However, this requires digital building models, which are rarely available. Consequently, these models must be created retrospectively, which is time-consuming when done manually. Naturally, there is a great interest in the industry to automate the process of retro-digitization. This paper contributes to these efforts by proposing a multistage pipeline to automatically extract the gradient of a bridge from pixel-based construction drawings using deep learning. The bridge gradient, a key element of the structure’s axis, is critical for describing the elevation profile and axis slope. This information is implicitly contained in the longitudinal view of bridge drawings as gradient symbols. To extract this information, the well-established object detection model YOLOv5 is employed to locate the gradient symbols inside the drawings. Subsequently, EasyOCR and heuristic rules are applied to extract the relevant gradient parameters associated with each detected symbol. The extracted parameters are then exported in a machine-interpretable format to facilitate seamless integration into other applications. The results show a promising 98% accuracy in symbol detection and an overall accuracy of 70%. Consequently, the pipeline represents a significant advance in automating the retro-digitization process for existing bridges by reducing the time and effort required
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Bayer, Hakan, Benedikt Faltin, and Markus König. "Automated Extraction of Bridge Gradient from Drawings Using Deep Learning." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/10.36253/979-12-215-0289-3.68.

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Digital methods such as Building Information Modeling (BIM) can be leveraged, to improve the efficiency of maintenance planning of bridges. However, this requires digital building models, which are rarely available. Consequently, these models must be created retrospectively, which is time-consuming when done manually. Naturally, there is a great interest in the industry to automate the process of retro-digitization. This paper contributes to these efforts by proposing a multistage pipeline to automatically extract the gradient of a bridge from pixel-based construction drawings using deep learning. The bridge gradient, a key element of the structure’s axis, is critical for describing the elevation profile and axis slope. This information is implicitly contained in the longitudinal view of bridge drawings as gradient symbols. To extract this information, the well-established object detection model YOLOv5 is employed to locate the gradient symbols inside the drawings. Subsequently, EasyOCR and heuristic rules are applied to extract the relevant gradient parameters associated with each detected symbol. The extracted parameters are then exported in a machine-interpretable format to facilitate seamless integration into other applications. The results show a promising 98% accuracy in symbol detection and an overall accuracy of 70%. Consequently, the pipeline represents a significant advance in automating the retro-digitization process for existing bridges by reducing the time and effort required
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Nguyen, Quoc-Son. "Quasi-static Evolution, Variational Principles and Implicit Scheme in Gradient Plasticity." In Springer Series in Solid and Structural Mechanics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-48884-4_7.

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Zhou, Jincheng, and Maoxing Zheng. "Federated Learning with Class Balanced Loss Optimized by Implicit Stochastic Gradient Descent." In Communications in Computer and Information Science. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0405-1_9.

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Medvedev, Dmitry, and Alexander D’yakonov. "Learning to Generate Synthetic Training Data Using Gradient Matching and Implicit Differentiation." In Communications in Computer and Information Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15168-2_12.

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Wu, Jiaying, Xiatao Kang, Jingying Xiao, and Jiayi Yao. "Gradient Coupled Flow: Performance Boosting on Network Pruning by Utilizing Implicit Loss Decrease." In Neural Information Processing. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-8082-6_18.

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Hahn, Jooyoung, Karol Mikula, Peter Frolkovič, and Branislav Basara. "Semi-implicit Level Set Method with Inflow-Based Gradient in a Polyhedron Mesh." In Springer Proceedings in Mathematics & Statistics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57394-6_9.

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Conference papers on the topic "Gradient implicite"

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Ngo, Tri, and Cornel Sultan. "Simulation of Helicopter Shipboard Operations with Spatial Velocity Gradients in the Ship's Airwake." In Vertical Flight Society 71st Annual Forum & Technology Display. The Vertical Flight Society, 2015. http://dx.doi.org/10.4050/f-0071-2015-10220.

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A mathematical model of a generic helicopter that captures essential helicopter-ship's airwake dynamics (e.g. fuselage dynamics, blade flapping and lead/lagging, interactional aerodynamic effects of the ship's airwake) has been developed in the implicit nonlinear ODE form for control design and evaluation. A procedure in which the ship's airwake characteristics with spatial velocity gradients are integrated into the rotor blade dynamics is described using polynomial interpolations from available CFD data. A simulation of the automatic lateral reposition toward the ship in 30-deg wind-over-deck
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Xu, Junyan, Jianxing Liao, Rucong Xu, and Yun Li. "GraDiNet: Implicit Self-Distillation of Graph Structural Knowledge." In 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2024. https://doi.org/10.1109/smc54092.2024.10831558.

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Lee, Donghyun, Jinhoon Wang, Beomsu Cho, and Junghyun Oh. "Enhancing Neural Implicit Representation-Based SLAM Performance through Depth Image Smoothing Utilizing Gradient-Aware Depth." In 2024 24th International Conference on Control, Automation and Systems (ICCAS). IEEE, 2024. https://doi.org/10.23919/iccas63016.2024.10773027.

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Nishikawa, Hiroaki. "Updates to Implicit Edge-Based Gradient Methods." In AIAA SCITECH 2024 Forum. American Institute of Aeronautics and Astronautics, 2024. http://dx.doi.org/10.2514/6.2024-1748.

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York, William D., and James H. Leylek. "Numerical Prediction of Mainstream Pressure Gradient Effects in Film Cooling." In ASME 1999 International Gas Turbine and Aeroengine Congress and Exhibition. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/99-gt-166.

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A documented, systematic, computational methodology is applied to singularly investigate the effects of mainstream pressure gradients on film cooling over a flat surface for realistic gas turbine parameters. Key aspects of the study include: (1) validation of the ability of computational fluid dynamics to simulate film cooling in regions of mainstream pressure gradients, accomplished through the isolation of this parameter and the careful modeling of a published experimental study; (2) documentation of the effects of the applied pressure gradient on film cooling adiabatic effectiveness, as com
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Ajmani, Kumud, and Meng-Sing Liou. "Implicit conjugate-gradient solvers on distributed-memory architectures." In 12th Computational Fluid Dynamics Conference. American Institute of Aeronautics and Astronautics, 1995. http://dx.doi.org/10.2514/6.1995-1695.

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Li, Peiyan, Xu Liang, and Haochen Song. "A Survey on Implicit Bias of Gradient Descent." In 2022 14th International Conference on Computer Research and Development (ICCRD). IEEE, 2022. http://dx.doi.org/10.1109/iccrd54409.2022.9730384.

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Yi, Sung-Jae, and Moon-Sun Chung. "An Advanced Semi-Implicit Method for Two-Phase Flow Calculation." In 2010 14th International Heat Transfer Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/ihtc14-22009.

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Introducing the interfacial pressure jump terms based on the surface tension into the momentum equations of two-phase two-fluid model, the system of governing equations is turned mathematically into the hyperbolic system. The eigenvalues of the equation system become always real representing the void wave and the pressure wave propagation speeds as shown in the present authors’ reference: Numerical Heat Transfer —Part B, vol. 40, pp. 83–97. To solve the interfacial pressure jump terms with void fraction gradients implicitly, the conventional semi-implicit method should be modified as an interm
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Nishikawa, Hiroaki. "Implicit Edge-Based Gradients for Simplex Grids." In AIAA AVIATION 2020 FORUM. American Institute of Aeronautics and Astronautics, 2020. http://dx.doi.org/10.2514/6.2020-3048.

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El Gheche, Mireille, Giovanni Chierchia, and Pascal Frossard. "Stochastic Gradient Descent for Spectral Embedding with Implicit Orthogonality Constraint." In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2019. http://dx.doi.org/10.1109/icassp.2019.8683286.

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