George A. Kevrekidis

1. Learning effective stochastic differential equations from microscopic simulations: linking stochastic numerics to deep learning
   2021/06/10 by Felix Dietrich, Dietrich, Felix, Alexei G. Makeev +9 · 13 citations
   Physics and Astronomy · #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks
2. On the Parameter Combinations That Matter and on Those That do Not
   2021/10/13 by Nikolaos Evangelou, Noah J. Wichrowski, Evangelou, Nikolaos +11 · 3 citations
   Computer Science · Physics and Astronomy · #37E99 (Primary) #68T07 (Secondary) #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications
3. Practical identifiability and parameter estimation of compartmental epidemiological models
   2024/06/25 by Q. Y. Chen, Chen, Q. Y., Zoi Rapti +9 · 1 citation
   Mathematics · #COVID-19 epidemiological studies #FOS: Computer and information sciences #Methodology (stat.ME)
4. Towards fully covariant machine learning
   2023/01/31 by Soledad Villar, Villar, Soledad, David W. Hogg +7 · 1 citation
   Computer Science · Decision Sciences · #Computational Physics and Python Applications #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Mathematical Physics (math-ph) #Scientific Computing and Data Management #Statistics and Probability (physics.data-an)
5. Neural Network Representations of Multiphase Equations of State
   2024/06/28 by George A. Kevrekidis, Daniel A. Serino, Kevrekidis, George A. +9 · 1 citation
   Computer Science · #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Neural Networks and Applications