3 papers
cs.CE2026
Latent Diffusion Posterior Sampling with Surrogate Likelihood Guidance for PDE Inverse Problems
Yuanzhe Wang, Alexandre M. Tartakovsky
We propose latent-space diffusion posterior sampling (L-DPS), an approximate Bayesian framework for high-dimensional inverse problems governed by partial differential equations (PD…
cs.AI2026
Discrete Diffusion for Complex and Congested Multi-Agent Path Finding with Sparse Social Attention
Yuanzhe Wang, Tian Zhi, Zihang Wei +8
Multi-Agent Path Finding (MAPF) is a coordination problem that requires computing globally consistent, collision-free trajectories from individual start positions to assigned goal…
cs.LG2024
Solving High-dimensional Inverse Problems Using Amortized Likelihood-free Inference with Noisy and Incomplete Data
Jice Zeng, Yuanzhe Wang, Alexandre M. Tartakovsky +1
We present a likelihood-free probabilistic inversion method based on normalizing flows for high-dimensional inverse problems. The proposed method is composed of two complementary n…