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12/02/2022
Identifying Hamiltonian manifold in neural networks
Recent studies to learn physical laws via deep learning attempt to find ...
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08/28/2022
Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network
Dynamical systems with interacting agents are universal in nature, commo...
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04/26/2022
Social learning spontaneously emerges by searching optimal heuristics with deep reinforcement learning
How have individuals of social animals in nature evolved to learn from e...
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02/15/2022
Quantifying team chemistry in scientific collaboration
Team chemistry is the holy grail of understanding collaborative human be...
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06/29/2021
Attaining entropy production and dissipation maps from Brownian movies via neural networks
Quantifying entropy production (EP) is essential to understand stochasti...
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02/08/2021
Discovering conservation laws from trajectories via machine learning
Invariants and conservation laws convey critical information about the u...
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11/20/2020
Deep Reinforcement Learning for Feedback Control in a Collective Flashing Ratchet
A collective flashing ratchet transports Brownian particles using a spat...
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03/09/2020
Learning entropy production via neural networks
This paper presents a neural estimator for entropy production, or NEEP, ...
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01/03/2020
Towards Automated Statistical Physics : Data-driven Modeling of Complex Systems with Deep Learning
Rich phenomena from complex systems have long intrigued researchers, and...
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01/25/2017