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HJ-sampler: A Bayesian sampler for inverse problems of a stochastic
  process by leveraging Hamilton-Jacobi PDEs and score-based generative models

HJ-sampler: A Bayesian sampler for inverse problems of a stochastic process by leveraging Hamilton-Jacobi PDEs and score-based generative models

15 September 2024
Tingwei Meng
Zongren Zou
Jérome Darbon
George Karniadakis
    DiffM
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Papers citing "HJ-sampler: A Bayesian sampler for inverse problems of a stochastic process by leveraging Hamilton-Jacobi PDEs and score-based generative models"

2 / 2 papers shown
Title
Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport
Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport
Zhenyi Zhang
Tiejun Li
Peijie Zhou
OT
141
5
0
01 Oct 2024
Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs
  Theory
Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory
T. Chen
Guan-Horng Liu
Evangelos A. Theodorou
DiffM
OT
174
162
0
21 Oct 2021
1