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Chaos (Woodbury, N.Y.)
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July 18, 2024
Transformations establishing equivalence across neural networks: When have two networks learned the same task?
Tom Bertalan, Felix Dietrich, Ioannis G Kevrekidis
Chaos (Woodbury, N.Y.)
|
January 3, 2020
On learning Hamiltonian systems from data
Tom Bertalan, Felix Dietrich, Igor Mezić, et al.
Frontiers in Computational Neuroscience
|
June 30, 2017
Coarse-Grained Descriptions of Dynamics for Networks with Both Intrinsic and Structural Heterogeneities
Tom Bertalan, Yan Wu, Carlo Laing, et al.
Iscience
|
July 31, 2025
Integration of Bayesian optimization and solution thermodynamics to optimize media design for mammalian biomanufacturing
Nelson Ndahiro, Edward Ma, Tom Bertalan, et al.
Frontiers in Computational Neuroscience
|
June 13, 2020
Emergent Spaces for Coupled Oscillators
Thomas N Thiem, Mahdi Kooshkbaghi, Tom Bertalan, et al.
Chaos (Woodbury, N.Y.)
|
October 2, 2021
Initializing LSTM internal states via manifold learning
Felix P Kemeth, Tom Bertalan, Nikolaos Evangelou, et al.
Chaos (Woodbury, N.Y.)
|
August 3, 2021
Global and local reduced models for interacting, heterogeneous agents
Thomas N Thiem, Felix P Kemeth, Tom Bertalan, et al.
Chaos (Woodbury, N.Y.)
|
March 1, 2023
Learning effective stochastic differential equations from microscopic simulations: Linking stochastic numerics to deep learning
Felix Dietrich, Alexei Makeev, George Kevrekidis, et al.
PNAS Nexus
|
June 19, 2026
Data-driven, ML-assisted approaches to problem well-posedness
Tom Bertalan, George A Kevrekidis, Eleni D Koronaki, et al.
Proceedings of the National Academy of Sciences of the United States of America
|
November 24, 2020
Local conformal autoencoder for standardized data coordinates
Erez Peterfreund, Ofir Lindenbaum, Felix Dietrich, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 12) with videos related to
Sort By:
Page
of 2
Chaos (Woodbury, N.Y.)
|
July 18, 2024
Transformations establishing equivalence across neural networks: When have two networks learned the same task?
Tom Bertalan, Felix Dietrich, Ioannis G Kevrekidis
Chaos (Woodbury, N.Y.)
|
January 3, 2020
On learning Hamiltonian systems from data
Tom Bertalan, Felix Dietrich, Igor Mezić, et al.
Frontiers in Computational Neuroscience
|
June 30, 2017
Coarse-Grained Descriptions of Dynamics for Networks with Both Intrinsic and Structural Heterogeneities
Tom Bertalan, Yan Wu, Carlo Laing, et al.
Iscience
|
July 31, 2025
Integration of Bayesian optimization and solution thermodynamics to optimize media design for mammalian biomanufacturing
Nelson Ndahiro, Edward Ma, Tom Bertalan, et al.
Frontiers in Computational Neuroscience
|
June 13, 2020
Emergent Spaces for Coupled Oscillators
Thomas N Thiem, Mahdi Kooshkbaghi, Tom Bertalan, et al.
Chaos (Woodbury, N.Y.)
|
October 2, 2021
Initializing LSTM internal states via manifold learning
Felix P Kemeth, Tom Bertalan, Nikolaos Evangelou, et al.
Chaos (Woodbury, N.Y.)
|
August 3, 2021
Global and local reduced models for interacting, heterogeneous agents
Thomas N Thiem, Felix P Kemeth, Tom Bertalan, et al.
Chaos (Woodbury, N.Y.)
|
March 1, 2023
Learning effective stochastic differential equations from microscopic simulations: Linking stochastic numerics to deep learning
Felix Dietrich, Alexei Makeev, George Kevrekidis, et al.
PNAS Nexus
|
June 19, 2026
Data-driven, ML-assisted approaches to problem well-posedness
Tom Bertalan, George A Kevrekidis, Eleni D Koronaki, et al.
Proceedings of the National Academy of Sciences of the United States of America
|
November 24, 2020
Local conformal autoencoder for standardized data coordinates
Erez Peterfreund, Ofir Lindenbaum, Felix Dietrich, et al.
Page
of 2