8 citations · 15 across the 15 of their papers we have counts for
15 papers
Adaptive Item-based Collaborative Structures via Noise Rescheduling in Diffusion for Generative Recommendation
Jiaqi Wang, Tianying Liu, Heng Chang +3
Discrete Diffusion Models (DDMs) have recently been introduced to recommendation systems, modeling user history as a token generation process via iterative denoising. However, whil…
Disentangling Generation and Regression in Stochastic Interpolants for Controllable Image Restoration
Yi Liu, Jia Ma, Wengen Li +3
Recent advances in Image Restoration (IR) have been largely driven by generative methods such as Diffusion Models and Flow Matching, which excel in synthesizing realistic textures…
SSDA: Bridging Spectral and Structural Gaps via Dual Adaptation for Vision-Based Time Series Forecasting
Mingrui Zhang, Hanchen Yang, Wengen Li +4
Large vision models (LVMs) have recently proven to be surprisingly effective time series forecasters, simply by rendering temporal data as images. This success, how ever, rests on…
AdaMamba: Adaptive Frequency-Gated Mamba for Long-Term Time Series Forecasting
Xudong Jiang, Mingshan Loo, Hanchen Yang +5
Accurate long-term time series forecasting (LTSF) requires the capture of complex long-range dependencies and dynamic periodic patterns. Recent advances in frequency-domain analysi…
An Adaptive Spatiotemporal Clustering Framework for 3D Ocean Subsurface Temperature Reconstruction
Ming Shan Loo, Wengen Li, Xudong Jiang +4
The reconstruction of ocean subsurface temperature (OST) using satellite remote sensing data holds significant scientific value for advancing the understanding of ocean dynamics an…
DiffTSP: A Conditional Discrete Diffusion Model for Knowledge Graph Triple Set Prediction
Jihong Guan, Jiaqi Wang, Wengen Li +5
Triple set prediction (TSP) aims to discover missing facts from an incomplete knowledge graph without predefined queries. Existing approaches typically construct the predicted set…
BioBridge: Bridging Proteins and Language for Enhanced Biological Reasoning with LLMs
Yujia Wang, Jihong Guan, Wengen Li +2
Existing Protein Language Models (PLMs) often suffer from limited adaptability to multiple tasks and exhibit poor generalization across diverse biological contexts. In contrast, ge…
SADER: Structure-Aware Diffusion Framework with DEterministic Resampling for Multi-Temporal Remote Sensing Cloud Removal
Yifan Zhang, Qian Chen, Yi Liu +2
Cloud contamination severely degrades the usability of remote sensing imagery and poses a fundamental challenge for downstream Earth observation tasks. Recently, diffusion-based mo…
scI2CL: Effectively Integrating Single-cell Multi-omics by Intra- and Inter-omics Contrastive Learning
Wuchao Liu, Han Peng, Wengen Li +3
Single-cell multi-omics data contain huge information of cellular states, and analyzing these data can reveal valuable insights into cellular heterogeneity, diseases, and biologica…
OKG-LLM: Aligning Ocean Knowledge Graph with Observation Data via LLMs for Global Sea Surface Temperature Prediction
Hanchen Yang, Jiaqi Wang, Jiannong Cao +7
Sea surface temperature (SST) prediction is a critical task in ocean science, supporting various applications, such as weather forecasting, fisheries management, and storm tracking…
Effective Cloud Removal for Remote Sensing Images by an Improved Mean-Reverting Denoising Model with Elucidated Design Space
Yi Liu, Wengen Li, Jihong Guan +2
Cloud removal (CR) remains a challenging task in remote sensing image processing. Although diffusion models (DM) exhibit strong generative capabilities, their direct applications t…
M-20M: A Large-Scale Multi-Modal Molecule Dataset for AI-driven Drug Design and Discovery
Siyuan Guo, Lexuan Wang, Chang Jin +6
This paper introduces M-20M, a large-scale Multi-Modal Molecule dataset that contains over 20 million molecules, with the data mainly being integrated from existing databases…
CorMulT: A Semi-supervised Modality Correlation-aware Multimodal Transformer for Sentiment Analysis
Yangmin Li, Ruiqi Zhu, Wengen Li
Multimodal sentiment analysis is an active research area that combines multiple data modalities, e.g., text, image and audio, to analyze human emotions and benefits a variety of ap…
CausalFormer: An Interpretable Transformer for Temporal Causal Discovery
Lingbai Kong, Wengen Li, Hanchen Yang +3
Temporal causal discovery is a crucial task aimed at uncovering the causal relations within time series data. The latest temporal causal discovery methods usually train deep learni…
Spatial-Temporal Data Mining for Ocean Science: Data, Methodologies, and Opportunities
Hanchen Yang, Wengen Li, Shuyu Wang +4
With the rapid amassing of spatial-temporal (ST) ocean data, many spatial-temporal data mining (STDM) studies have been conducted to address various oceanic issues, including clima…