Bibliography
Chanussot, L., Das, A., Goyal, S., Lavril, T., Shuaibi, M., Riviere, M., Tran, K., Heras-Domingo, J., Ho, C., Hu, W., Palizhati, A., Sriram, A., Wood, B., Yoon, J., Parikh, D., Zitnick, C. L., & Ulissi, Z. (2021). Open Catalyst 2020 (OC20) Dataset and Community Challenges. ACS Catalysis, 11(10), 6059â6072.
Authors
17
- Lowik Chanussot (first)
- Abhishek Das (additional)
- Siddharth Goyal (additional)
- Thibaut Lavril (additional)
- Muhammed Shuaibi (additional)
- Morgane Riviere (additional)
- Kevin Tran (additional)
- Javier Heras-Domingo (additional)
- Caleb Ho (additional)
- Weihua Hu (additional)
- Aini Palizhati (additional)
- Anuroop Sriram (additional)
- Brandon Wood (additional)
- Junwoong Yoon (additional)
- Devi Parikh (additional)
- C. Lawrence Zitnick (additional)
- Zachary Ulissi (additional)
References
103
Referenced
423
{'volume-title': 'Global Energy Outlook 2020: Energy Transition or Energy Addition? With Commentary on Implications of the COVID-19 Pandemic', 'year': '2020', 'author': 'Newell R. G.', 'key': 'ref1/cit1'}
/ Global Energy Outlook 2020: Energy Transition or Energy Addition? With Commentary on Implications of the COVID-19 Pandemic by Newell R. G. (2020){'volume-title': 'Annual Energy Outlook 2020', 'year': '2020', 'key': 'ref2/cit2'}
/ Annual Energy Outlook 2020 (2020)-
Nørskov, J. K.; Studt, F.; Abild-Pedersen, F.; Bligaard, T. Fundamental Concepts in Heterogeneous Catalysis; John Wiley & Sons, 2014; pp 1–4.
(
10.1002/9781118892114
) 10.1126/science.aad4998
10.1002/anie.201208487
/ The Catalyst Genome by Nørskov J. K. (2013)-
Sholl, D. S.; Steckel, J. A. Density Functional Theory; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2009; pp 1–31.
(
10.1002/9780470447710
) 10.1021/acscatal.9b01234
10.1021/acscatal.8b01708
10.1038/ncomms14621
10.1039/c9me00078j
10.1039/c7re00210f
10.1016/j.energy.2019.116091
10.1021/acs.jpclett.9b03657
10.1007/s40192-018-0108-9
10.1088/2632-2153/ab7e1a
10.1038/s41929-018-0142-1
10.1021/acs.jpclett.0c00634
10.1021/acs.jpclett.9b01428
10.1021/acs.chemmater.9b03686
10.1016/j.chempr.2020.09.001
10.1021/jacs.7b11239
10.1016/j.cad.2019.05.038
10.3389/fbuil.2020.00059
10.1038/s41524-019-0221-0
10.1007/978-3-030-29829-6_2
/ Impact: Design with All Senses by Aksöz Z. (2020)10.1080/08927022.2016.1274984
10.1016/j.cpc.2016.05.010
10.1063/1.4960708
10.1021/acs.jctc.9b00465
10.1021/acscatal.9b03599
10.1038/s41929-018-0056-y
10.1038/s41929-018-0150-1
10.1002/aic.16198
10.1002/cctc.201900595
/ ChemCatChem by Schlexer Lamoureux P. (2019)10.3390/catal7100306
10.1038/s41578-018-0005-z
10.1002/aenm.201903242
10.1088/2515-7655/ab2060
10.1039/c9ta02356a
10.1021/acscatal.9b04186
10.1002/adma.201907865
10.1002/cctc.201900595
10.1002/cctc.201900595
10.1016/j.commatsci.2012.02.002
10.1038/npjcompumats.2015.10
/ npj Comput. Mater. by Kirklin S. (2015)10.1002/anie.201402958
10.1103/physrevlett.99.016105
10.1103/physrevlett.118.036101
10.1039/c7sc03422a
10.1021/acscatal.8b04478
10.1016/j.susc.2018.11.019
10.1039/c7ta01812f
10.1016/j.joule.2018.12.015
10.1038/s41597-019-0080-z
10.1038/s41597-019-0081-y
/ Sci. Data by Winther K. T. (2019)-
Deng, J.; Dong, W.; Socher, R.; Li, L.J.; Li, K.; Fei-Fei, L. Imagenet: A large-scale hierarchical image database. 2009 IEEE Conference on Computer Vision and Pattern Recognition; IEEE, 2009; pp 248–255.
(
10.1109/CVPR.2009.5206848
) -
Panayotov, V.; Chen, G.; Povey, D.; Khudanpur, S. Librispeech: an asr corpus based on public domain audio books. 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP); IEEE, 2015; pp 5206–5210.
(
10.1109/ICASSP.2015.7178964
) -
Antol, S.; Agrawal, A.; Lu, J.; Mitchell, M.; Batra, D.; Lawrence Zitnick, C.; Parikh, D. Vqa: Visual question answering. Proceedings of the IEEE International Conference on Computer Vision; IEEE, 2015; pp 2425–2433.
(
10.1109/ICCV.2015.279
) 10.1063/1.4812323
10.1016/j.commatsci.2005.04.010
- Bader, R.; Bader, R. Atoms In Molecules: A Quantum Theory; International Series of Monographs on Chemistry; Clarendon Press, 1994; pp 13–52.
10.1038/s41570-020-0189-9
/ Nat. Rev. Chem. by von Lilienfeld O. A. (2020)10.1016/j.commatsci.2012.10.028
10.1021/acs.jpca.9b00311
{'key': 'ref65/cit65', 'first-page': '273002', 'volume': '29', 'author': 'Larsen A. H.', 'year': '2017', 'journal-title': 'J. Phys.: Condens. Matter'}
/ J. Phys.: Condens. Matter by Larsen A. H. (2017)10.1103/physrevb.49.14251
10.1016/0927-0256(96)00008-0
10.1103/physrevb.54.11169
10.1103/physrevb.59.1758
10.1103/physrevlett.77.3865
10.1088/0953-8984/21/8/084204
10.1002/jcc.20575
10.1002/jcc.26353
10.1021/jp202489s
10.1103/physrevb.100.184103
10.1038/s41524-020-0310-0
10.1038/s41524-019-0162-7
10.1038/s41524-020-00401-8
/ npj Comput. Mater. by Kim Y. (2019)10.1039/c8me00012c
- Fey, M.; Lenssen, J. E.; Fast graph representation learning with PyTorch Geometric. 2019, arXiv preprint arXiv:1903.02428.
- Paszke, A.; Gross, S.; Massa, F.; Lerer, A.; Bradbury, J.; Chanan, G.; Killeen, T.; Lin, Z.; Gimelshein, N.; Antiga, L.; Pytorch: An imperative style, high-performance deep learning library. Advances in Neural Information Processing Systems 2019, pp 8026–8037.
{'volume-title': 'Representation Learning on Graphs: Methods and Applications', 'year': '2017', 'author': 'Hamilton W. L.', 'key': 'ref83/cit83'}
/ Representation Learning on Graphs: Methods and Applications by Hamilton W. L. (2017)10.1063/1.4966192
10.1103/physrevlett.104.136403
10.1103/physrevlett.120.145301
{'key': 'ref87/cit87', 'first-page': '991', 'author': 'Schütt K.', 'year': '2017', 'journal-title': 'Adv. Neural Inf. Process. Syst.'}
/ Adv. Neural Inf. Process. Syst. by Schütt K. (2017)- Klicpera, J.; Giri, S.; Margraf, J. T.; Günnemann, S. Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules. 2020, arXiv preprint arXiv:2011.14115.
- Klicpera, J.; Groß, J.; Günnemann, S. Directional Message Passing for Molecular Graphs. International Conference on Learning Representations (ICLR), 2020.
10.1038/sdata.2014.22
-
Pracht, P.; Caldeweyher, E.; Ehlert, S.; Grimme, S.;A Robust Non-Self-Consistent Tight-Binding Quantum Chemistry Method for large Molecules. 2019, chemrxiv:8326202.v1.
(
10.26434/chemrxiv.8326202
) 10.1002/wcms.1493
10.1063/1.3095491
10.1007/bf01589116
-
Tang, Y.; Selvitopi, O.; Popovici, D. T.; Buluç, A. A High-Throughput Solver for Marginalized Graph Kernels on GPU. 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS); IEEE, 2020; pp 728–738.
(
10.1109/IPDPS47924.2020.00080
) 10.1063/1.5078640
- Huang, B.; Symonds, N. O.; von Lilienfeld, O. A. The fundamentals of quantum machine learning. 2018, arXiv preprint arXiv:1807.04259.
- Miller, B. K.; Geiger, M.; Smidt, T. E.; Noé, F. Relevance of Rotationally Equivariant Convolutions for Predicting Molecular Properties. 2020, arXiv preprint arXiv:2008.08461.
-
Bratholm, L. A.; Gerrard, W.; Anderson, B.; Bai, S.; Choi, S.; Dang, L.; Hanchar, P.; Howard, A.; Huard, G.; Kim, S.; A community-powered search of machine learning strategy space to find NMR property prediction models. 2020, arXiv preprint arXiv:2008.05994.
(
10.1371/journal.pone.0253612
) {'key': 'ref100/cit100', 'first-page': '14537', 'author': 'Anderson B.', 'year': '2019', 'journal-title': 'Adv. Neural Inf. Process. Syst.'}
/ Adv. Neural Inf. Process. Syst. by Anderson B. (2019)10.1063/5.0021116
10.1002/anie.201107947
-
He, K.; Zhang, X.; Ren, S.; Sun, J. Deep residual learning for image recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016; pp 770–778.
(
10.1109/CVPR.2016.90
) {'key': 'ref104/cit104', 'first-page': '9', 'volume': '1', 'author': 'Radford A.', 'year': '2019', 'journal-title': 'OpenAI Blog'}
/ OpenAI Blog by Radford A. (2019)
Dates
Type | When |
---|---|
Created | 4 years, 3 months ago (May 4, 2021, 12:41 p.m.) |
Deposited | 2 years, 4 months ago (April 15, 2023, 7:20 a.m.) |
Indexed | 1 minute ago (Aug. 21, 2025, 3:17 a.m.) |
Issued | 4 years, 3 months ago (May 4, 2021) |
Published | 4 years, 3 months ago (May 4, 2021) |
Published Online | 4 years, 3 months ago (May 4, 2021) |
Published Print | 4 years, 3 months ago (May 21, 2021) |
@article{Chanussot_2021, title={Open Catalyst 2020 (OC20) Dataset and Community Challenges}, volume={11}, ISSN={2155-5435}, url={http://dx.doi.org/10.1021/acscatal.0c04525}, DOI={10.1021/acscatal.0c04525}, number={10}, journal={ACS Catalysis}, publisher={American Chemical Society (ACS)}, author={Chanussot, Lowik and Das, Abhishek and Goyal, Siddharth and Lavril, Thibaut and Shuaibi, Muhammed and Riviere, Morgane and Tran, Kevin and Heras-Domingo, Javier and Ho, Caleb and Hu, Weihua and Palizhati, Aini and Sriram, Anuroop and Wood, Brandon and Yoon, Junwoong and Parikh, Devi and Zitnick, C. Lawrence and Ulissi, Zachary}, year={2021}, month=may, pages={6059–6072} }