Eric Vanden‐Eijnden

Physics and Astronomy · Physical Sciences

67h-index18.1kcitations275works1.82yr avg
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Research Topics

Advanced Thermodynamics and Statistical Mechanics(54), Protein Structure and Dynamics(45), Spectroscopy and Quantum Chemical Studies(40), Theoretical and Computational Physics(36), Model Reduction and Neural Networks(26)

Publications275 total

Effect of Local Topological Changes on Resistance in Tunably-Disordered Networks
ArXiv.org·2026Open Access
Effect of Local Topological Changes on Resistance in Tunably-Disordered Networks
arXiv (Cornell University)·2026Open Access
Generative Modeling from Black-box Corruptions via Self-Consistent Stochastic Interpolants
arXiv (Cornell University)·2025Open Access
Dynamic Test-Time Compute Scaling in Control Policy: Difficulty-Aware Stochastic Interpolant Policy
arXiv (Cornell University)·2025Open Access
Model-Free Learning of Probability Flows: Elucidating the Nonequilibrium Dynamics of Flocking
Physical Review Letters·2025· 1 cited
Scale-Adaptive Generative Flows for Multiscale Scientific Data
arXiv (Cornell University)·2025Open Access
Lipschitz-Guided Design of Interpolation Schedules in Generative Models
arXiv (Cornell University)·2025Open Access
How to build a consistency model: Learning flow maps via self-distillation
arXiv (Cornell University)·2025Open Access
FEAT: Free energy Estimators with Adaptive Transport
arXiv (Cornell University)·2025Open Access
Optimizing Noise Schedules of Generative Models in High Dimensionss
arXiv (Cornell University)·2025Open Access
Model-free learning of probability flows: Elucidating the nonequilibrium dynamics of flocking
arXiv (Cornell University)·2024Open Access
Learning to sample better
Journal of Statistical Mechanics Theory and Experiment·2024
Efficient training of energy-based models using Jarzynski equality<sup>*</sup>
Journal of Statistical Mechanics Theory and Experiment·2024· 1 citedOpen Access
An Efficient On-Policy Deep Learning Framework for Stochastic Optimal Control
arXiv (Cornell University)·2024Open Access
NETS: A Non-Equilibrium Transport Sampler
arXiv (Cornell University)·2024Open Access
Unveiling the Phase Diagram and Reaction Paths of the Active Model B with the Deep Minimum Action Method
Physical Review Letters·2024· 2 citedOpen Access
Flow map matching with stochastic interpolants: A mathematical framework for consistency models
arXiv (Cornell University)·2024Open Access
Deep learning probability flows and entropy production rates in active matter
Proceedings of the National Academy of Sciences·2024· 23 citedOpen Access
Issue Information ‐ TOC
Communications on Pure and Applied Mathematics·2024Open Access
Sequential-in-time training of nonlinear parametrizations for solving time-dependent partial differential equations
arXiv (Cornell University)·2024· 1 citedOpen Access
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Frequent Co-authors

E Weinan(17), Weiqing Ren(8), Giovanni Ciccotti(6), Luca Maragliano(5), Christof Schütte(4), Björn Engquist(3), Maddalena Venturoli(3), Frank Noé(2), Xiantao Li(2), Philipp Metzner(2), Tiejun Li(2), Andrew J. Majda(2), Di Liu(2), Cyrill B. Muratov(2), Grant M. Rotskoff(2), Lothar Reich(1), Thomas R. Weikl(1), Alexander Fischer(1), Assyr Abdulle(1), Carmen Hijón(1)