🏢 Westlake University

Samba: a novel severity-aware recurrent model, tackles cross-domain medical image grading by sequentially encoding image patches and recalibrating states using EM, significantly improving accuracy.

ProtGO: A novel unified framework integrating protein sequence, structure & function for superior representation learning, significantly outperforming current methods.

FADA: a novel frequency-adapted learning scheme boosts domain-generalized semantic segmentation by decoupling style and content using Haar wavelets, achieving state-of-the-art results.

RELA accelerates representation learning by leveraging freely available pre-trained models to generate efficient data, reducing computational costs by up to 50% while maintaining accuracy.

DiffPhyCon uses diffusion models to generate near-optimal control sequences for complex physical systems, outperforming existing methods by simultaneously optimizing a generative energy function and c…

PSNR, a novel node-adaptive residual module, significantly improves deep GNN performance by mitigating over-smoothing and handling missing data.

AdaNovo tackles data biases in de novo peptide sequencing by using Conditional Mutual Information, significantly improving PTM identification and overall accuracy.