3 citations · 3 across the 2 of their papers we have counts for
3 papers
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…
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…
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…