421 citations · 1.2k across the 38 of their papers we have counts for
4 papers · 1 filter
Deepmechanics
Abhay Shinde, Aryan Amit Barsainyan, Jose Siguenza +3
Physics-informed deep learning models have emerged as powerful tools for learning dynamical systems. These models directly encode physical principles into network architectures. Ho…
AgriVariant: Variant Effect Prediction using DeepChem-Variant for Precision Breeding in Rice
Ankita Vaishnobi Bisoi, Bharath Ramsundar
Predicting functional consequences of genetic variants in crop genes remains a critical bottleneck for precision breeding programs. We present AgriVariant, an end-to-end pipeline f…
A fully differentiable framework for training proxy Exchange Correlation Functionals for periodic systems
Rakshit Kumar Singh, Aryan Amit Barsainyan, Bharath Ramsundar
Density Functional Theory (DFT) is widely used for first-principles simulations in chemistry and materials science, but its computational cost remains a key limitation for large sy…
Protect: Steerable Retrosynthesis through Neuro-Symbolic State Encoding
Shreyas Vinaya Sathyanarayana, Shah Rahil Kirankumar, Sharanabasava D. Hiremath +1
Large Language Models (LLMs) have shown remarkable potential in scientific domains like retrosynthesis; yet, they often lack the fine-grained control necessary to navigate complex…