Literatura académica sobre el tema "Machine Learning Informé"
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Artículos de revistas sobre el tema "Machine Learning Informé"
Shoureshi, R., D. Swedes, and R. Evans. "Learning Control for Autonomous Machines." Robotica 9, no. 2 (1991): 165–70. http://dx.doi.org/10.1017/s0263574700010201.
Texto completoPateras, Joseph, Pratip Rana, and Preetam Ghosh. "A Taxonomic Survey of Physics-Informed Machine Learning." Applied Sciences 13, no. 12 (2023): 6892. http://dx.doi.org/10.3390/app13126892.
Texto completoMinasny, Budiman, Toshiyuki Bandai, Teamrat A. Ghezzehei, et al. "Soil Science-Informed Machine Learning." Geoderma 452 (December 2024): 117094. http://dx.doi.org/10.1016/j.geoderma.2024.117094.
Texto completoXypakis, Emmanouil, Valeria deTurris, Fabrizio Gala, Giancarlo Ruocco, and Marco Leonetti. "Physics-informed machine learning for microscopy." EPJ Web of Conferences 266 (2022): 04007. http://dx.doi.org/10.1051/epjconf/202226604007.
Texto completoZhao, Hefei, Yinglun Zhan, Joshua Nduwamungu, Yuzhen Zhou, Changmou Xu, and Zheng Xu. "Machine learning-driven Raman spectroscopy for rapidly detecting type, adulteration, and oxidation of edible oils." INFORM International News on Fats, Oils, and Related Materials 31, no. 4 (2020): 12–15. http://dx.doi.org/10.21748/inform.04.2020.12.
Texto completoSerre, Thomas. "Deep Learning: The Good, the Bad, and the Ugly." Annual Review of Vision Science 5, no. 1 (2019): 399–426. http://dx.doi.org/10.1146/annurev-vision-091718-014951.
Texto completoArundel, Samantha T., Gaurav Sinha, Wenwen Li, David P. Martin, Kevin G. McKeehan, and Philip T. Thiem. "Historical maps inform landform cognition in machine learning." Abstracts of the ICA 6 (August 11, 2023): 1–2. http://dx.doi.org/10.5194/ica-abs-6-10-2023.
Texto completoKarimpouli, Sadegh, and Pejman Tahmasebi. "Physics informed machine learning: Seismic wave equation." Geoscience Frontiers 11, no. 6 (2020): 1993–2001. http://dx.doi.org/10.1016/j.gsf.2020.07.007.
Texto completoOneto, Luca, Sandro Ridella, and Davide Anguita. "Informed Machine Learning: Excess risk and generalization." Neurocomputing 646 (September 2025): 130521. https://doi.org/10.1016/j.neucom.2025.130521.
Texto completoZhang, Xi. "Application of Machine Learning in Stock Price Analysis." Highlights in Science, Engineering and Technology 107 (August 15, 2024): 143–49. http://dx.doi.org/10.54097/tjhsx998.
Texto completoTesis sobre el tema "Machine Learning Informé"
Guimbaud, Jean-Baptiste. "Enhancing Environmental Risk Scores with Informed Machine Learning and Explainable AI." Electronic Thesis or Diss., Lyon 1, 2024. http://www.theses.fr/2024LYO10188.
Texto completoDoumèche, Nathan. "Physics-informed machine learning : a mathematical framework with applications to time series forecasting." Electronic Thesis or Diss., Sorbonne université, 2025. http://www.theses.fr/2025SORUS105.
Texto completoQuattromini, Michele. "Graph Neural Networks for fluid mechanics : data-assimilation and optimization." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPAST161.
Texto completoMack, Jonas. "Physics Informed Machine Learning of Nonlinear Partial Differential Equations." Thesis, Uppsala universitet, Tillämpad matematik och statistik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-441275.
Texto completoLeung, Jason W. "Application of machine learning : automated trading informed by event driven data." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/105982.
Texto completoWu, Jinlong. "Predictive Turbulence Modeling with Bayesian Inference and Physics-Informed Machine Learning." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/85129.
Texto completoElabid, Zakaria. "Informed deep learning for modeling physical dynamics." Electronic Thesis or Diss., Sorbonne université, 2025. http://www.theses.fr/2025SORUS006.
Texto completoReichert, Nils. "CORRELATION BETWEEN COMPUTER RECOGNIZED FACIAL EMOTIONS AND INFORMED EMOTIONS DURING A CASINO COMPUTER GAME." Thesis, Fredericton: University of New Brunswick, 2012. http://hdl.handle.net/1882/44596.
Texto completoWang, Jianxun. "Physics-Informed, Data-Driven Framework for Model-Form Uncertainty Estimation and Reduction in RANS Simulations." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/77035.
Texto completoCedergren, Linnéa. "Physics-informed Neural Networks for Biopharma Applications." Thesis, Umeå universitet, Institutionen för fysik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-185423.
Texto completoLibros sobre el tema "Machine Learning Informé"
Schulz, Daniel, and Christian Bauckhage, eds. Informed Machine Learning. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-83097-6.
Texto completoHuang, Qiang. Domain-informed Machine Learning for Smart Manufacturing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-91631-1.
Texto completoInterpretable Machine Learning for the Analysis, Design, Assessment, and Informed Decision Making for Civil Infrastructure. Elsevier Science & Technology, 2023.
Buscar texto completoMadhu, G., Sandeep Kautish, A. Govardhan, and Avinash Sharma, eds. Emerging Computational Approaches in Telehealth and Telemedicine: A Look at The Post-COVID-19 Landscape. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/97898150792721220101.
Texto completoSmith, Gary, and Jay Cordes. The 9 Pitfalls of Data Science. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198844396.001.0001.
Texto completoAnderson, Raymond A. Credit Intelligence & Modelling. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192844194.001.0001.
Texto completoEl-Nasr, Magy Seif, Alessandro Canossa, Truong-Huy D. Nguyen, and Anders Drachen. Game Data Science. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192897879.001.0001.
Texto completoDowd, Cate. Digital Journalism, Drones, and Automation. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190655860.001.0001.
Texto completoOulasvirta, Antti, Per Ola Kristensson, Xiaojun Bi, and Andrew Howes, eds. Computational Interaction. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198799603.001.0001.
Texto completoGiudici, Paolo, and Giulio Mignola. Big Data & Advanced Analytics per il Risk Management. AIFIRM, 2022. http://dx.doi.org/10.47473/2016ppa00035.
Texto completoCapítulos de libros sobre el tema "Machine Learning Informé"
Bauckhage, Christian, and Rafet Sifa. "Training Support Vector Machines by Solving Differential Equations." In Cognitive Technologies. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-83097-6_12.
Texto completoNeuer, Marcus J. "Physics-Informed Learning." In Machine Learning for Engineers. Springer Berlin Heidelberg, 2024. http://dx.doi.org/10.1007/978-3-662-69995-9_6.
Texto completoBraga-Neto, Ulisses. "Physics-Informed Machine Learning." In Fundamentals of Pattern Recognition and Machine Learning. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-60950-3_12.
Texto completoWang, Sifan, and Paris Perdikaris. "Adaptive Training Strategies for Physics-Informed Neural Networks." In Knowledge-Guided Machine Learning. Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003143376-6.
Texto completoSimm, Jaak, Adam Arany, Edward De Brouwer, and Yves Moreau. "Expressive Graph Informer Networks." In Machine Learning, Optimization, and Data Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95470-3_15.
Texto completoTsironis, Giorgos. "Epidemiology with Physics Informed Machine Learning." In Understanding Complex Systems. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-81946-9_18.
Texto completoAfroze, Lameya, Silke Merkelbach, Sebastian von Enzberg, and Roman Dumitrescu. "Domain Knowledge Injection Guidance for Predictive Maintenance." In Machine Learning for Cyber-Physical Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-47062-2_8.
Texto completoSun, Alexander Y., Hongkyu Yoon, Chung-Yan Shih, and Zhi Zhong. "Applications of Physics-Informed Scientific Machine Learning in Subsurface Science: A Survey." In Knowledge-Guided Machine Learning. Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003143376-5.
Texto completoHuang, Qiang. "Applications of Process-Informed Optimal Compensation." In Domain-informed Machine Learning for Smart Manufacturing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-91631-1_7.
Texto completoDani, Harsh, Jundong Li, and Huan Liu. "Sentiment Informed Cyberbullying Detection in Social Media." In Machine Learning and Knowledge Discovery in Databases. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71249-9_4.
Texto completoActas de conferencias sobre el tema "Machine Learning Informé"
Oneto, Luca, Nicolò Navarin, Alessio Micheli, et al. "Informed Machine Learning for Complex Data." In ESANN 2024. Ciaco - i6doc.com, 2024. http://dx.doi.org/10.14428/esann/2024.es2024-1.
Texto completoOneto, Luca, Davide Anguita, and Sandro Ridella. "Informed Machine Learning: Excess Risk and Generalization." In ESANN 2024. Ciaco - i6doc.com, 2024. http://dx.doi.org/10.14428/esann/2024.es2024-20.
Texto completoOsorio Quero, Carlos Alexander, and Jose Martinez-Carranza. "Physics-Informed Machine Learning for UAV Control." In 2024 21st International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE). IEEE, 2024. https://doi.org/10.1109/cce62852.2024.10770871.
Texto completoFarlessyost, William, and Shweta Singh. "Improving Mechanistic Model Accuracy with Machine Learning Informed Physics." In Foundations of Computer-Aided Process Design. PSE Press, 2024. http://dx.doi.org/10.69997/sct.121371.
Texto completoYu, Yue, Jiageng Tong, Jinhui Xia, Jinya Su, and Shihua Li. "PMSM System Identification by Knowledge-informed Machine Learning." In 2024 IEEE 22nd International Conference on Industrial Informatics (INDIN). IEEE, 2024. https://doi.org/10.1109/indin58382.2024.10774223.
Texto completoZhu, Shijie, Hao Li, Yejie Jiang, and Yingjun Deng. "Inner Defect Detection via Physics-Informed Machine Learning." In 2024 6th International Conference on System Reliability and Safety Engineering (SRSE). IEEE, 2024. https://doi.org/10.1109/srse63568.2024.10772527.
Texto completoZhang, Tianren, Yuanbin Wang, Ruizhe Dong, Wenhu Wang, Zhongxue Yang, and Mingzhu Zhu. "Informed Machine Learning for Real-time Grinding Force Prediction." In 2024 30th International Conference on Mechatronics and Machine Vision in Practice (M2VIP). IEEE, 2024. http://dx.doi.org/10.1109/m2vip62491.2024.10746047.
Texto completoLiu, Zheng, Yuan Jiang, Yumeng Li, and Pingfeng Wang. "Physics-Informed Machine Learning for Battery Pack Thermal Management." In 2025 Annual Reliability and Maintainability Symposium (RAMS). IEEE, 2025. https://doi.org/10.1109/rams48127.2025.10935157.
Texto completoSampath, Akila, Omar Faruque, Azim Khan, Vandana Janeja, and Jianwu Wang. "Physics-Informed Machine Learning for Sea Ice Thickness Prediction." In 2024 IEEE International Conference on Knowledge Graph (ICKG). IEEE, 2024. https://doi.org/10.1109/ickg63256.2024.00048.
Texto completoPark, Taegyun, Eunkoo Lee, Sol Han, et al. "Chemistry-informed machine learning model for EUV photoresist development." In Advances in Patterning Materials and Processes XLII, edited by Douglas Guerrero and Ryan Callahan. SPIE, 2025. https://doi.org/10.1117/12.3049907.
Texto completoInformes sobre el tema "Machine Learning Informé"
Martinez, Carianne, Jessica Jones, Drew Levin, Nathaniel Trask, and Patrick Finley. Physics-Informed Machine Learning for Epidemiological Models. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1706217.
Texto completoMcDermott, Jason, Song Feng, Christine Chang, Darren Schmidt, and Vincent Danna. Structural- and Functional-Informed Machine Learning for Protein Function Prediction. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1988630.
Texto completoGuthrie, George Drake Jr, and Hari S. Viswanathan. Science-informed Machine Learning to Increase Recovery Efficiency in Unconventional Reservoirs. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1614818.
Texto completoWang, Jianxun, Jinlong Wu, Julia Ling, Gianluca Iaccarino, and Heng Xiao. Physics-Informed Machine Learning for Predictive Turbulence Modeling: Towards a Complete Framework. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1562229.
Texto completoBailey Bond, Robert, Pu Ren, James Fong, Hao Sun, and Jerome F. Hajjar. Physics-informed Machine Learning Framework for Seismic Fragility Analysis of Steel Structures. Northeastern University, 2024. http://dx.doi.org/10.17760/d20680141.
Texto completoPasupuleti, Murali Krishna. Mathematical Modeling for Machine Learning: Theory, Simulation, and Scientific Computing. National Education Services, 2025. https://doi.org/10.62311/nesx/rriv125.
Texto completoMueller, Juliane. Machine Learning to Enable Efficient Uncertainty Quantification, Data Assimilation, and Informed Data Acquisition. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1769743.
Texto completoAthon, Matthew, Danielle Ciesielski, Jordan Corbey, et al. Visualizing Uranium Crystallization from Melt: Experiment-Informed Phase Field Modeling and Machine Learning. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/2338176.
Texto completoHeo, YeongAe, Joshua Humberston, and Jose Barreras Gonzalez. Evolving Multi-hazard Machine Learning Modeling for Advanced Risk-Informed Infrastructure Resilience Assessment. Office of Scientific and Technical Information (OSTI), 2024. https://doi.org/10.2172/2483390.
Texto completoUllrich, Paul, Tapio Schneider, and Da Yang. Physics-Informed Machine Learning from Observations for Clouds, Convection, and Precipitation Parameterizations and Analysis. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1769762.
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