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Adeesh Kolluru
Adeesh Kolluru
PhD Student, Carnegie Mellon University
Verified email at andrew.cmu.edu - Homepage
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Cited by
Year
The Open Catalyst 2022 (OC22) dataset and challenges for oxide electrocatalysts
R Tran, J Lan, M Shuaibi, BM Wood, S Goyal, A Das, J Heras-Domingo, ...
ACS Catalysis 13 (5), 3066-3084, 2023
852023
Rotation invariant graph neural networks using spin convolutions
M Shuaibi, A Kolluru, A Das, A Grover, A Sriram, Z Ulissi, CL Zitnick
arXiv preprint arXiv:2106.09575, 2021
672021
Spherical channels for modeling atomic interactions
L Zitnick, A Das, A Kolluru, J Lan, M Shuaibi, A Sriram, Z Ulissi, B Wood
Advances in Neural Information Processing Systems 35, 8054-8067, 2022
372022
Open challenges in developing generalizable large-scale machine-learning models for catalyst discovery
A Kolluru, M Shuaibi, A Palizhati, N Shoghi, A Das, B Wood, CL Zitnick, ...
ACS Catalysis 12 (14), 8572-8581, 2022
302022
Transfer learning using attentions across atomic systems with graph neural networks (TAAG)
A Kolluru, N Shoghi, M Shuaibi, S Goyal, A Das, CL Zitnick, Z Ulissi
The Journal of Chemical Physics 156 (18), 2022
212022
From molecules to materials: Pre-training large generalizable models for atomic property prediction
N Shoghi, A Kolluru, JR Kitchin, ZW Ulissi, CL Zitnick, BM Wood
arXiv preprint arXiv:2310.16802, 2023
72023
Materials cartography: A forward-looking perspective on materials representation and devising better maps
SB Torrisi, MZ Bazant, AE Cohen, MG Cho, JS Hummelshøj, L Hung, ...
APL Machine Learning 1 (2), 2023
62023
The Open Catalyst Challenge 2021: Competition Report.
A Das, M Shuaibi, A Palizhati, S Goyal, A Grover, A Kolluru, J Lan, A Rizvi, ...
NeurIPS (Competition and Demos), 29-40, 2021
22021
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