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2020 – today
- 2024
[j1]Soledad Villar, David W. Hogg, Weichi Yao, George A. Kevrekidis, Bernhard Schölkopf:
Towards fully covariant machine learning. Trans. Mach. Learn. Res. 2024 (2024)- [i7]George A. Kevrekidis, Eleni D. Koronaki, Yannis G. Kevrekidis:
Conformal Disentanglement: A Neural Framework for Perspective Synthesis and Differentiation. CoRR abs/2408.15344 (2024) - [i6]George A. Kevrekidis, Mauro Maggioni, Soledad Villar, Yannis G. Kevrekidis:
Thinner Latent Spaces: Detecting dimension and imposing invariance through autoencoder gradient constraints. CoRR abs/2408.16138 (2024) - 2023
- [i5]Soledad Villar, David W. Hogg, Weichi Yao, George A. Kevrekidis, Bernhard Schölkopf:
The passive symmetries of machine learning. CoRR abs/2301.13724 (2023) - [i4]Nikolaos Evangelou, Dimitrios G. Giovanis, George A. Kevrekidis, Grigorios A. Pavliotis, Ioannis G. Kevrekidis:
Machine Learning for the identification of phase-transitions in interacting agent-based systems. CoRR abs/2310.19039 (2023) - 2022
- [i3]Nabeel Sarwar, Wilson Gregory, George A. Kevrekidis, Soledad Villar, Bianca Dumitrascu:
MarkerMap: nonlinear marker selection for single-cell studies. CoRR abs/2207.14106 (2022) - 2021
- [i2]Felix Dietrich, Alexei Makeev, George Kevrekidis, Nikolaos Evangelou, Tom Bertalan, Sebastian Reich, Ioannis G. Kevrekidis:
Learning effective stochastic differential equations from microscopic simulations: combining stochastic numerics and deep learning. CoRR abs/2106.09004 (2021) - [i1]Nikolaos Evangelou, Noah J. Wichrowski, George A. Kevrekidis, Felix Dietrich, Mahdi Kooshkbaghi, Sarah McFann, Ioannis G. Kevrekidis:
On the Parameter Combinations That Matter and on Those That do Not. CoRR abs/2110.06717 (2021)
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