11 citations · 25 across the 6 of their papers we have counts for
6 papers
PGODE: Towards High-quality System Dynamics Modeling
Xiao Luo, Yiyang Gu, Huiyu Jiang +6
This paper studies the problem of modeling multi-agent dynamical systems, where agents could interact mutually to influence their behaviors. Recent research predominantly uses geom…
Weisfeiler and Leman Go Measurement Modeling: Probing the Validity of the WL Test
Arjun Subramonian, Adina Williams, Maximilian Nickel +2
The expressive power of graph neural networks is usually measured by comparing how many pairs of graphs or nodes an architecture can possibly distinguish as non-isomorphic to those…
A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware
Shichang Zhang, Atefeh Sohrabizadeh, Cheng Wan +7
Graph neural networks (GNNs) are emerging for machine learning research on graph-structured data. GNNs achieve state-of-the-art performance on many tasks, but they face scalability…
Learning Probabilities of Causation from Finite Population Data
Ang Li, Song Jiang, Yizhou Sun +1
This paper deals with the problem of learning the probabilities of causation of subpopulations given finite population data. The tight bounds of three basic probabilities of causat…
Unsupervised Adversarially-Robust Representation Learning on Graphs
Jiarong Xu, Yang Yang, Junru Chen +4
Unsupervised/self-supervised pre-training methods for graph representation learning have recently attracted increasing research interests, and they are shown to be able to generali…
Differentiable Product Quantization for End-to-End Embedding Compression
Ting Chen, Lala Li, Yizhou Sun
Embedding layers are commonly used to map discrete symbols into continuous embedding vectors that reflect their semantic meanings. Despite their effectiveness, the number of parame…