5 papers
Accelerating Locality-Driven Integration in Quantum Chemistry with Block-Structured Matrix Multiplication
Xinran Wei, Yan Pan, Fusong Ju +8
Locality-driven integration is a pervasive computational pattern in quantum chemistry, arising whenever spatially localized basis functions interact through numerical quadrature or…
E2Former: An Efficient and Equivariant Transformer with Linear-Scaling Tensor Products
Yunyang Li, Lin Huang, Zhihao Ding +10
Equivariant Graph Neural Networks (EGNNs) have demonstrated significant success in modeling microscale systems, including those in chemistry, biology and materials science. However…
UniGenX: a unified generative foundation model that couples sequence, structure and function to accelerate scientific design across proteins, molecules and materials
Gongbo Zhang, Yanting Li, Renqian Luo +31
Function in natural systems arises from one-dimensional sequences forming three-dimensional structures with specific properties. However, current generative models suffer from crit…
HybriDNA: A Hybrid Transformer-Mamba2 Long-Range DNA Language Model
Mingqian Ma, Guoqing Liu, Chuan Cao +12
Advances in natural language processing and large language models have sparked growing interest in modeling DNA, often referred to as the "language of life". However, DNA modeling…
Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning
Yuxuan Ren, Dihan Zheng, Chang Liu +7
In recent years, machine learning has demonstrated impressive capability in handling molecular science tasks. To support various molecular properties at scale, machine learning mod…