4 papers
Fixed-Dimensional Latent Flow for Generating Variable-Size 3D Molecules
Weichi Yao, Cameron Gruich, Bryan R. Goldsmith +1
Molecular size is intrinsically linked to composition, structure, and properties, but most 3D molecular generators treat size as a predefined input rather than a quantity to be gen…
Adapting Evidential Neural Networks to Test-Time Neighbor Fusion Improves Molecular Property Prediction
Cameron Gruich, Weichi Yao, Yixin Wang +1
A trained molecular property model can be refined at test time by correcting each prediction with the measured labels of the most similar training molecules, a retraining-free proc…
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…
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…