2.3k citations · 9.6k across the 47 of their papers we have counts for
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Convergence of the Deep BSDE Method for Coupled FBSDEs
Jiequn Han, Jihao Long
The recently proposed numerical algorithm, deep BSDE method, has shown remarkable performance in solving high-dimensional forward-backward stochastic differential equations (FBSDEs…
A Mean-Field Optimal Control Formulation of Deep Learning
Weinan E, Jiequn Han, Qianxiao Li
Recent work linking deep neural networks and dynamical systems opened up new avenues to analyze deep learning. In particular, it is observed that new insights can be obtained by re…
Solving Many-Electron Schrödinger Equation Using Deep Neural Networks
Jiequn Han, Linfeng Zhang, Weinan E
We introduce a new family of trial wave-functions based on deep neural networks to solve the many-electron Schrödinger equation. The Pauli exclusion principle is dealt with explici…
End-to-end Symmetry Preserving Inter-atomic Potential Energy Model for Finite and Extended Systems
Linfeng Zhang, Jiequn Han, Han Wang +3
Machine learning models are changing the paradigm of molecular modeling, which is a fundamental tool for material science, chemistry, and computational biology. Of particular inter…
DeePCG: constructing coarse-grained models via deep neural networks
Linfeng Zhang, Jiequn Han, Han Wang +2
We introduce a general framework for constructing coarse-grained potential models without ad hoc approximations such as limiting the potential to two- and/or three-body contributio…