6 papers
Flow Matching Transport for Quasi-Monte Carlo Integration
Zhijun Zeng, Jianlong Chen
High-dimensional integration with respect to complex target measures remains a fundamental challenge in computational science. While Flow Matching (FM) offers a powerful paradigm f…
BlinDNO: A Distributional Neural Operator for Dynamical System Reconstruction from Time-Label-Free data
Zhijun Zeng, Junqing Chen, Zuoqiang Shi
We study an inverse problem for stochastic and quantum dynamical systems in a time-label-free setting, where only unordered density snapshots sampled at unknown times drawn from an…
An Efficient Conditional Score-based Filter for High Dimensional Nonlinear Filtering Problems
Zhijun Zeng, Weiye Gan, Junqing Chen +1
In many engineering and applied science domains, high-dimensional nonlinear filtering is still a challenging problem. Recent advances in score-based diffusion models offer a promis…
Kernel Variational Inference Flow for Nonlinear Filtering Problem
Weiye Gan, Zhijun Zeng, Junqing Chen +1
We present a novel particle flow for sampling called kernel variational inference flow (KVIF). KVIF do not require the explicit formula of the target distribution which is usually…
OpenBreastUS: Benchmarking Neural Operators for Wave Imaging Using Breast Ultrasound Computed Tomography
Zhijun Zeng, Youjia Zheng, Hao Hu +8
Accurate and efficient simulation of wave equations is crucial in computational wave imaging applications, such as ultrasound computed tomography (USCT), which reconstructs tissue…
Robust Frequency Domain Full-Waveform Inversion via HV-Geometry
Zhijun Zeng, Matej Neumann, Yunan Yang
Conventional frequency-domain full-waveform inversion (FWI) is typically implemented with an misfit function, which suffers from challenges such as cycle skipping and sensiti…