4 citations · 16 across the 12 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
cs.LG2023
Physics-Informed Generator-Encoder Adversarial Networks with Latent Space Matching for Stochastic Differential Equations
Ruisong Gao, Min Yang, Jin Zhang
We propose a new class of physics-informed neural networks, called Physics-Informed Generator-Encoder Adversarial Networks, to effectively address the challenges posed by forward,…
cs.LG2023★ 2 cited
PI-VEGAN: Physics Informed Variational Embedding Generative Adversarial Networks for Stochastic Differential Equations
Ruisong Gao, Yufeng Wang, Min Yang +1
We present a new category of physics-informed neural networks called physics informed variational embedding generative adversarial network (PI-VEGAN), that effectively tackles the…