1 citations · 1 across the 10 of their papers we have counts for
13 papers
Imaging-101: Benchmarking LLM Coding Agents on Scientific Computational Imaging
Siyi Chen, Jiahe Ying, Yixuan Jia +9
Computational imaging, which recovers hidden signals from indirect, noisy measurements, underpins quantitative discovery across scientific disciplines, yet building a correct recon…
Constant-Target Energy Matching: A Unified Framework for Continuous and Discrete Density Estimation
Zhijun Zeng, Yixuan Jiang, Pipi Hu +1
Density estimation is a central primitive in probabilistic modeling, yet continuous, discrete, and mixed-variable domains are often treated by separate objectives, limiting the abi…
Deep-Picard Iteration for Space-time Fractional Diffusion PDEs
Zhijun Zeng, Zhitong Chen, Ling Qin +1
We propose a Deep-Picard iteration framework for high-dimensional nonlinear space-time fractional diffusion equations.The method is based on a nonlinear fractional Feynman--Kac fix…
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…
Ultrasound Tomography of Musculoskeletal Tissues with Generative Neural Physics
Zhijun Zeng, Youjia Zheng, Chang Su +10
Ultrasound Tomography (UT) is a radiation-free, high-resolution modality, but remains limited for musculoskeletal imaging due to the high computational cost and instability of full…
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…
Weak Collocation Regression for Inferring Stochastic Dynamics with Lévy Noise
Liya Guo, Liwei Lu, Zhijun Zeng +2
With the rapid increase of observational, experimental and simulated data for stochastic systems, tremendous efforts have been devoted to identifying governing laws underlying the…
Neural Born Series Operator for Biomedical Ultrasound Computed Tomography
Zhijun Zeng, Yihang Zheng, Youjia Zheng +3
Ultrasound Computed Tomography (USCT) provides a radiation-free option for high-resolution clinical imaging. Despite its potential, the computationally intensive Full Waveform Inve…
Reconstruction of dynamical systems from data without time labels
Zhijun Zeng, Pipi Hu, Chenglong Bao +2
In this paper, we study the method to reconstruct dynamical systems from data without time labels. Data without time labels appear in many applications, such as molecular dynamics,…