2.4k citations · 6.2k across the 17 of their papers we have counts for
6 papers · 1 filter
FedGKD: Unleashing the Power of Collaboration in Federated Graph Neural Networks
Qiying Pan, Ruofan Wu, Tengfei Liu +3
Federated training of Graph Neural Networks (GNN) has become popular in recent years due to its ability to perform graph-related tasks under data isolation scenarios while preservi…
Rapid Image Labeling via Neuro-Symbolic Learning
Yifeng Wang, Zhi Tu, Yiwen Xiang +4
The success of Computer Vision (CV) relies heavily on manually annotated data. However, it is prohibitively expensive to annotate images in key domains such as healthcare, where da…
The Effect of Masking Strategies on Knowledge Retention by Language Models
Jonas Wallat, Tianyi Zhang, Avishek Anand
Language models retain a significant amount of world knowledge from their pre-training stage. This allows knowledgeable models to be applied to knowledge-intensive tasks prevalent…
Neural Frailty Machine: Beyond proportional hazard assumption in neural survival regressions
Ruofan Wu, Jiawei Qiao, Mingzhe Wu +5
We present neural frailty machine (NFM), a powerful and flexible neural modeling framework for survival regressions. The NFM framework utilizes the classical idea of multiplicative…
Human-in-the-Loop Schema Induction
Tianyi Zhang, Isaac Tham, Zhaoyi Hou +12
Schema induction builds a graph representation explaining how events unfold in a scenario. Existing approaches have been based on information retrieval (IR) and information extract…
Efficient Graph Field Integrators Meet Point Clouds
Krzysztof Choromanski, Arijit Sehanobish, Han Lin +13
We present two new classes of algorithms for efficient field integration on graphs encoding point clouds. The first class, SeparatorFactorization(SF), leverages the bounded genus o…