1 citations · 1 across the 4 of their papers we have counts for
6 papers
A Fixed-Point Neural Operator for Size- and Functional-Transferable Hamiltonian Prediction
Yunhong Lou, Xihang Yue, Xinran Wei +2
Predicting the Kohn-Sham Hamiltonian with machine learning can accelerate density functional theory while retaining access to molecular orbitals, energy levels, and electronic-stru…
PDEAgent-Bench: A Multi-Metric, Multi-Library Benchmark for PDE Solver Generation
Zhen Hang, Yushan Yashengjiang, Junhui Li +21
PDE-to-solver code generation aims to automatically synthesize executable numerical solvers from partial differential equation (PDE) specifications. This task requires not only und…
Holistic Physics Solver: Learning PDEs in a Unified Spectral-Physical Space
Xihang Yue, Yi Yang, Linchao Zhu
Recent advances in operator learning have produced two distinct approaches for solving partial differential equations (PDEs): attention-based methods offering point-level adaptabil…
FragRel: Exploiting Fragment-level Relations in the External Memory of Large Language Models
Xihang Yue, Linchao Zhu, Yi Yang
To process contexts with unlimited length using Large Language Models (LLMs), recent studies explore hierarchically managing the long text. Only several text fragments are taken fr…
DeltaPhi: Physical States Residual Learning for Neural Operators in Data-Limited PDE Solving
Xihang Yue, Yi Yang, Linchao Zhu
The limited availability of high-quality training data poses a major obstacle in data-driven PDE solving, where expensive data collection and resolution constraints severely impact…
Efficient Emotional Adaptation for Audio-Driven Talking-Head Generation
Yuan Gan, Zongxin Yang, Xihang Yue +2
Audio-driven talking-head synthesis is a popular research topic for virtual human-related applications. However, the inflexibility and inefficiency of existing methods, which neces…