3 papers
cs.LG2026
Measuring Progress in Reasoning Toward Mathematical Discovery with Automatic Verification
Erik Y. Wang, Sumeet R. Motwani, James V. Roggeveen +9
Can AI make progress on important, unsolved mathematical problems? Large language models are now capable of sophisticated mathematical and scientific reasoning, but whether they ca…
q-bio.GN2025
Modeling Gene Expression Distributional Shifts for Unseen Genetic Perturbations
Kalyan Ramakrishnan, Jonathan G. Hedley, Sisi Qu +5
We train a neural network to predict distributional responses in gene expression following genetic perturbations. This is an essential task in early-stage drug discovery, where suc…
cs.LG2025
Implicit Neural Representations for Chemical Reaction Paths
Kalyan Ramakrishnan, Lars L. Schaaf, Chen Lin +2
We show that neural networks can be optimized to represent minimum energy paths as continuous functions, offering a flexible alternative to discrete path-search methods such as Nud…