1 code implementation • 7 May 2024 • Adeesh Kolluru, John R Kitchin
Given the novelty of this framework and application, we provide insights into the impact of pre-training, model architectures, and conduct extensive experiments to underscore the significance of this approach.
1 code implementation • 25 Oct 2023 • Nima Shoghi, Adeesh Kolluru, John R. Kitchin, Zachary W. Ulissi, C. Lawrence Zitnick, Brandon M. Wood
Similar success in atomic property prediction has been limited due to the challenges of training effective models across multiple chemical domains.
2 code implementations • 29 Jun 2022 • C. Lawrence Zitnick, Abhishek Das, Adeesh Kolluru, Janice Lan, Muhammed Shuaibi, Anuroop Sriram, Zachary Ulissi, Brandon Wood
We propose the Spherical Channel Network (SCN) to model atomic energies and forces.
1 code implementation • 17 Jun 2022 • Richard Tran, Janice Lan, Muhammed Shuaibi, Brandon M. Wood, Siddharth Goyal, Abhishek Das, Javier Heras-Domingo, Adeesh Kolluru, Ammar Rizvi, Nima Shoghi, Anuroop Sriram, Felix Therrien, Jehad Abed, Oleksandr Voznyy, Edward H. Sargent, Zachary Ulissi, C. Lawrence Zitnick
The development of machine learning models for electrocatalysts requires a broad set of training data to enable their use across a wide variety of materials.
1 code implementation • 17 Jun 2021 • Muhammed Shuaibi, Adeesh Kolluru, Abhishek Das, Aditya Grover, Anuroop Sriram, Zachary Ulissi, C. Lawrence Zitnick
We introduce a novel approach to modeling angular information between sets of neighboring atoms in a graph neural network.
Ranked #3 on Initial Structure to Relaxed Energy (IS2RE) on OC20
Graph Neural Network Initial Structure to Relaxed Energy (IS2RE)