activity
20102024
most citedSkeleton-Based Action Recognition with Spatial Reasoning and Temporal Stack Learning

32 citations · 256 across the 40 of their papers we have counts for

collaborators

41 papers

q-bio.BM2024★ 26 cited

DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design

Jiaqi Guan, Xiangxin Zhou, Yuwei Yang +6

Designing 3D ligands within a target binding site is a fundamental task in drug discovery. Existing structured-based drug design methods treat all ligand atoms equally, which ignor…

physics.chem-ph2023★ 2 cited

Uncovering Neural Scaling Laws in Molecular Representation Learning

Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang +5

Molecular Representation Learning (MRL) has emerged as a powerful tool for drug and materials discovery in a variety of tasks such as virtual screening and inverse design. While th…

cs.LG2023★ 21 cited

OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling

Yi-Fan Zhang, Qingsong Wen, Xue Wang +6

Online updating of time series forecasting models aims to address the concept drifting problem by efficiently updating forecasting models based on streaming data. Many algorithms a…

cs.CV2023

Multi-Semantic Fusion Model for Generalized Zero-Shot Skeleton-Based Action Recognition

Ming-Zhe Li, Zhen Jia, Zhang Zhang +2

Generalized zero-shot skeleton-based action recognition (GZSSAR) is a new challenging problem in computer vision community, which requires models to recognize actions without any t…

cs.LG2023

TCGF: A unified tensorized consensus graph framework for multi-view representation learning

Xiangzhu Meng, Wei Wei, Qiang Liu +2

Multi-view learning techniques have recently gained significant attention in the machine learning domain for their ability to leverage consistency and complementary information acr…

cs.AI2023

TiBGL: Template-induced Brain Graph Learning for Functional Neuroimaging Analysis

Xiangzhu Meng, Wei Wei, Qiang Liu +2

In recent years, functional magnetic resonance imaging has emerged as a powerful tool for investigating the human brain's functional connectivity networks. Related studies demonstr…