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20242026
most citedInvariant Graph Representations for Continuous-Time Dynamic Graphs Under Distribution Shifts

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2026

DEFUSE: Generalizable Backdoor Defense for Self-Supervised Encoders with Generative Priors

Tuo Chen, Jie Gui, Minjing Dong +4

Self-supervised learning (SSL) encoders are vulnerable to backdoor attacks, posing threats to both visual SSL encoders and vision-language encoders. Existing defenses are typically…

cs.CV2025

Backdooring Self-Supervised Contrastive Learning by Noisy Alignment

Tuo Chen, Jie Gui, Minjing Dong +3

Self-supervised contrastive learning (CL) effectively learns transferable representations from unlabeled data containing images or image-text pairs but suffers vulnerability to dat…

cs.AI2024

PORCA: Root Cause Analysis with Partially Observed Data

Chang Gong, Di Yao, Jin Wang +6

Root Cause Analysis (RCA) aims at identifying the underlying causes of system faults by uncovering and analyzing the causal structure from complex systems. It has been widely used…

cs.LG2024★ 1 cited

Invariant Graph Representations for Continuous-Time Dynamic Graphs Under Distribution Shifts

Lanting Fang, Yulian Yang, Yawei Zhang +3

Continuous-Time Dynamic Graphs (CTDGs) enable fine-grained modeling of evolving relational systems. However, most existing CTDG representation learning methods are tailored to in-d…

cs.LG2024

AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models

Shuo Liu, Di Yao, Lanting Fang +5

Detecting anomaly edges for dynamic graphs aims to identify edges significantly deviating from the normal pattern and can be applied in various domains, such as cybersecurity, fina…