46 citations · 100 across the 13 of their papers we have counts for
19 papers
Global Counterfactual Explainer for Graph Neural Networks
Mert Kosan, Zexi Huang, Sourav Medya +2
Graph neural networks (GNNs) find applications in various domains such as computational biology, natural language processing, and computer security. Owing to their popularity, ther…
Mind Reader: Reconstructing complex images from brain activities
Sikun Lin, Thomas Sprague, Ambuj K Singh
Understanding how the brain encodes external stimuli and how these stimuli can be decoded from the measured brain activities are long-standing and challenging questions in neurosci…
Modeling Human-AI Team Decision Making
Wei Ye, Francesco Bullo, Noah Friedkin +1
AI and humans bring complementary skills to group deliberations. Modeling this group decision making is especially challenging when the deliberations include an element of risk and…
A Broader Picture of Random-walk Based Graph Embedding
Zexi Huang, Arlei Silva, Ambuj Singh
Graph embedding based on random-walks supports effective solutions for many graph-related downstream tasks. However, the abundance of embedding literature has made it increasingly…
Learning Interpretable Models for Coupled Networks Under Domain Constraints
Hongyuan You, Sikun Lin, Ambuj K. Singh
Modeling the behavior of coupled networks is challenging due to their intricate dynamics. For example in neuroscience, it is of critical importance to understand the relationship b…
DANR: Discrepancy-aware Network Regularization
Hongyuan You, Furkan Kocayusufoglu, Ambuj K. Singh
Network regularization is an effective tool for incorporating structural prior knowledge to learn coherent models over networks, and has yielded provably accurate estimates in appl…