2.3k citations · 9.6k across the 47 of their papers we have counts for
Showing 2019Show all
3 papers · 1 filter
math.OC2019★ 29 cited
Deep Fictitious Play for Finding Markovian Nash Equilibrium in Multi-Agent Games
Jiequn Han, Ruimeng Hu
We propose a deep neural network-based algorithm to identify the Markovian Nash equilibrium of general large -player stochastic differential games. Following the idea of fictiti…
math.NA2019★ 7 cited
Universal approximation of symmetric and anti-symmetric functions
Jiequn Han, Yingzhou Li, Lin Lin +3
We consider universal approximations of symmetric and anti-symmetric functions, which are important for applications in quantum physics, as well as other scientific and engineering…
physics.comp-ph2019★ 90 cited
Uniformly Accurate Machine Learning Based Hydrodynamic Models for Kinetic Equations
Jiequn Han, Chao Ma, Zheng Ma +1
A new framework is introduced for constructing interpretable and truly reliable reduced models for multiscale problems in situations without scale separation. Hydrodynamic approxim…