4 papers
Fixed-Dimensional Latent Flow for Generating Variable-Size 3D Molecules
Weichi Yao, Cameron Gruich, Bryan R. Goldsmith +1
In molecular discovery, molecule size is coupled to composition, structure, and other target properties. Yet most 3D generators require molecule size to be specified before generat…
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…