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Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_wB97MV Data Set.

A. Garrison, J. Heras-Domingo, J. Kitchin, G. dos Passos Gomes, Z. Ulissi, and S. Blau. J. Chem. Inf. Model., 63 (24): 7642-7654 (December 2023)

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Zachary Dotscheff

Zachary Evenson

Zachary Hayes

Zachary Taylor

Zachary J Evenson

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Cluster-MLP: An Active Learning Genetic Algorithm Framework for Accelerated Discovery of Global Minimum Configurations of Pure and Alloyed Nanoclusters.R. Raju, S. Sivakumar, X. Wang, and Z. Ulissi. J. Chem. Inf. Model., 63 (20): 6192-6197 (October 2023)AmpTorch: A Python package for scalable fingerprint-based neural network training on multi-element systems with integrated uncertainty quantification.M. Shuaibi, Y. Hu, X. Lei, B. Comer, M. Adams, J. Paras, R. Chen, E. Musa, J. Musielewicz, A. Peterson and 2 other author(s). J. Open Source Softw., 8 (87): 5035 (2023)Deep reinforcement learning for predicting kinetic pathways to surface reconstruction in a ternary alloy.J. Yoon, Z. Cao, R. Raju, Y. Wang, R. Burnley, A. Gellman, A. Farimani, and Z. Ulissi. Mach. Learn. Sci. Technol., 2 (4): 45018 (2021)The Open Catalyst Challenge 2021: Competition Report.A. Das, M. Shuaibi, A. Palizhati, S. Goyal, A. Grover, A. Kolluru, J. Lan, A. Rizvi, A. Sriram, B. Wood and 15 other author(s). NeurIPS (Competition and Demos), volume 176 of Proceedings of Machine Learning Research, page 29-40. PMLR, (2021)GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets.J. Gasteiger, M. Shuaibi, A. Sriram, S. Günnemann, Z. Ulissi, C. Zitnick, and A. Das. Trans. Mach. Learn. Res., (2022)The Open Catalyst 2020 (OC20) Dataset and Community Challenges.L. Chanussot, A. Das, S. Goyal, T. Lavril, M. Shuaibi, M. Riviere, K. Tran, J. Heras-Domingo, C. Ho, W. Hu and 7 other author(s). CoRR, (2020)Rotation Invariant Graph Neural Networks using Spin Convolutions.M. Shuaibi, A. Kolluru, A. Das, A. Grover, A. Sriram, Z. Ulissi, and C. Zitnick. CoRR, (2021)Spherical Channels for Modeling Atomic Interactions.L. Zitnick, A. Das, A. Kolluru, J. Lan, M. Shuaibi, A. Sriram, Z. Ulissi, and B. Wood. NeurIPS, (2022)Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_wB97MV Data Set.A. Garrison, J. Heras-Domingo, J. Kitchin, G. dos Passos Gomes, Z. Ulissi, and S. Blau. J. Chem. Inf. Model., 63 (24): 7642-7654 (December 2023)The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysis.R. Tran, J. Lan, M. Shuaibi, S. Goyal, B. Wood, A. Das, J. Heras-Domingo, A. Kolluru, A. Rizvi, N. Shoghi and 3 other author(s). CoRR, (2022)

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Disambiguation of "Ulissi, Zachary W."

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Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_wB97MV Data Set.

Please choose a person to relate this publication to

Zachary Dotscheff

Zachary Evenson

Zachary Hayes

Zachary Taylor

Zachary J Evenson

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Ulissi, Zachary W."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_wB97MV Data Set.

Please choose a person to relate this publication to

Zachary Dotscheff

Zachary Evenson

Zachary Hayes

Zachary Taylor

Zachary J Evenson

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_wB97MV Data Set.