evidential neural networks 1molecular property prediction 1neighbor fusion 1test-time adaptation 1uncertainty quantification 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.LG2026
Adapting Evidential Neural Networks to Test-Time Neighbor Fusion Improves Molecular Property Prediction
Cameron Gruich, Weichi Yao, Yixin Wang +1
The paper introduces PG‑EVIKAL, a method that refines molecular property predictions at test time by fusing predictions with labels of similar training molecules, using evidential…
physics.chem-ph2026
TSAgent: An Agentic Workflow for Autonomous Transition State Search
Varun Madhavan, Ankit Mathanker, Dean M. Sweeney +3
Identifying transition states (TSs) on potential energy surfaces is a central computational bottleneck in mechanistic studies of catalytic materials. A TS search is not a single ca…
stat.ML2026
Goal-Oriented Influence-Maximizing Data Acquisition for Learning and Optimization
Weichi Yao, Bianca Dumitrascu, Bryan R. Goldsmith +1
Active data acquisition is central to many learning and optimization tasks in deep neural networks, yet remains challenging because most approaches rely on predictive uncertainty e…