421 citations · 1.2k across the 38 of their papers we have counts for
19 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…
DeepChem Equivariant: SE(3)-Equivariant Support in an Open-Source Molecular Machine Learning Library
Jose Siguenza, Bharath Ramsundar
Neural networks that incorporate geometric relationships respecting SE(3) group transformations (e.g. rotations and translations) are increasingly important in molecular applicatio…
Open-Source Protein Language Models for Function Prediction and Protein Design
Shivasankaran Vanaja Pandi, Bharath Ramsundar
Protein language models (PLMs) have shown promise in improving the understanding of protein sequences, contributing to advances in areas such as function prediction and protein eng…
Open source Differentiable ODE Solving Infrastructure
Rakshit Kr. Singh, Aaron Rock Menezes, Rida Irfan +1
Ordinary Differential Equations (ODEs) are widely used in physics, chemistry, and biology to model dynamic systems, including reaction kinetics, population dynamics, and biological…
Open Source Infrastructure for Automatic Cell Segmentation
Aaron Rock Menezes, Bharath Ramsundar
Automated cell segmentation is crucial for various biological and medical applications, facilitating tasks like cell counting, morphology analysis, and drug discovery. However, man…
Open-Source Molecular Processing Pipeline for Generating Molecules
V Shreyas, Jose Siguenza, Karan Bania +1
Generative models for molecules have shown considerable promise for use in computational chemistry, but remain difficult to use for non-experts. For this reason, we introduce open-…