1 citations · 1 across the 3 of their papers we have counts for
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Graph Anomaly Detection as Finite-Horizon Control: Training-Free Scoring via Empirical Bayes
Fred Xu, Thomas Markovich, Florence Regol +1
Node-level graph anomaly detection (GAD) identifies nodes whose attributes and interactions deviate from dominant graph regularities. Existing GAD models encode normality and anoma…
Improving Function Space Flow Matching with Kernel Optimal Transport
Fred Xu, Thomas Markovich, Barbora Barancikova +1
Generative models for function-valued data, such as time series and solutions of partial differential equations, must learn distributions over infinite-dimensional spaces. Function…
A Unified Uncertainty Representation for Graph Neural Networks via Doubly-Spectral Stochastic Expansion
Fred Xu, Thomas Markovich, Florence Regol +1
Reliable deployment of graph neural networks requires calibration, out-of-distribution (OOD) detection, and robustness to distribution shift, yet existing methods address these nee…