1 citations · 1 across the 5 of their papers we have counts for
6 papers
SINO: Scale-Invariant Neural Operator
Kaichen Ouyang, Chenglei Yu, Chuanrui Wang +1
In scientific machine learning, physical fields governed by partial differential equations exhibit low-rank structure and scale invariance. When solving equations on coarse grids,…
Path Integral Value Matching for Linear Quadratic Stochastic Optimal Control
Bangyan Liao, Chenglei Yu, Yuchen Yang +4
Linear Quadratic Stochastic Optimal Control (LQ-SOC) establishes a fundamental framework for steering noisy dynamical systems and has recently gained renewed interest in the machin…
PACE: Geometry-Aware Bridge Transport for Single-Cell Trajectory Inference
Chenglei Yu, Chuanrui Wang, Bangyan Liao +1
Single-cell trajectory inference from destructive time-course snapshots is fundamentally ill-posed: neither cross-time cell correspondences nor continuous trajectories are observed…
RealPDEBench: A Benchmark for Complex Physical Systems with Real-World Data
Peiyan Hu, Haodong Feng, Hongyuan Liu +13
Predicting the evolution of complex physical systems remains a central problem in science and engineering. Despite rapid progress in scientific Machine Learning (ML) models, a crit…
scDFM: Distributional Flow Matching Model for Robust Single-Cell Perturbation Prediction
Chenglei Yu, Chuanrui Wang, Bangyan Liao +1
A central goal in systems biology and drug discovery is to predict the transcriptional response of cells to perturbations. This task is challenging due to the noisy and sparse natu…
GGBall: Graph Generative Model on Poincaré Ball
Tianci Bu, Chuanrui Wang, Hao Ma +3
Generating graphs with hierarchical structures remains a fundamental challenge due to the limitations of Euclidean geometry in capturing exponential complexity. Here we introduce \…