5 papers
From Accuracy to Auditability: A Survey of Determinism in Financial AI Systems
Ruizhe Zhou, Xiaoyang Liu, Gaoyuan Du +4
Deploying machine learning in regulated financial environments -- credit risk, fraud detection, and anti-money laundering -- exposes critical vulnerabilities in algorithmic reprodu…
SPADE: Faster Drug Discovery by Learning from Sparse Data
Rahul Nandakumar, Ben Fauber, Deepayan Chakrabarti
Drug discovery seeks molecules (ligands) that bind strongly and selectively to a target protein. However, fewer than 5% of candidate ligands pass the bar for even the early stages…
COPYCOP: Ownership Verification for Graph Neural Networks
Rahul Nandakumar, Deepayan Chakrabarti
Given two GNNs that output node embeddings, how can we determine if they were trained independently? An adversary could have trained one GNN specifically to mimic the other GNN's e…
Learning to Query History: Nonstationary Classification via Learned Retrieval
Jimmy Gammell, Bishal Thapaliya, Yoon Jung +3
Nonstationarity is ubiquitous in practical classification settings, leading deployed models to perform poorly even when they generalize well to holdout sets available at training t…
GraphWeave: Interpretable and Robust Graph Generation via Random Walk Trajectories
Rahul Nandakumar, Deepayan Chakrabarti
Given a set of graphs from some unknown family, we want to generate new graphs from that family. Recent methods use diffusion on either graph embeddings or the discrete space of no…