12 citations · 28 across the 11 of their papers we have counts for
11 papers
Lossless data compression by large models
Ziguang Li, Chao Huang, Xuliang Wang +7
Modern data compression methods are slowly reaching their limits after 80 years of research, millions of papers, and wide range of applications. Yet, the extravagant 6G communicati…
Predicting mutational effects on protein-protein binding via a side-chain diffusion probabilistic model
Shiwei Liu, Tian Zhu, Milong Ren +3
Many crucial biological processes rely on networks of protein-protein interactions. Predicting the effect of amino acid mutations on protein-protein binding is vital in protein eng…
A Theory of Human-Like Few-Shot Learning
Zhiying Jiang, Rui Wang, Dongbo Bu +1
We aim to bridge the gap between our common-sense few-sample human learning and large-data machine learning. We derive a theory of human-like few-shot learning from von-Neuman-Land…
NIERT: Accurate Numerical Interpolation through Unifying Scattered Data Representations using Transformer Encoder
Shizhe Ding, Boyang Xia, Milong Ren +1
Interpolation for scattered data is a classical problem in numerical analysis, with a long history of theoretical and practical contributions. Recent advances have utilized deep ne…
Seq-SetNet: Exploring Sequence Sets for Inferring Structures
Fusong Ju, Jianwei Zhu, Guozheng Wei +3
Sequence set is a widely-used type of data source in a large variety of fields. A typical example is protein structure prediction, which takes an multiple sequence alignment (MSA)…
Predicting protein inter-residue contacts using composite likelihood maximization and deep learning
Haicang Zhang, Qi Zhang, Fusong Ju +7
Accurate prediction of inter-residue contacts of a protein is important to calcu- lating its tertiary structure. Analysis of co-evolutionary events among residues has been proved e…