Views provided by UsageCounts
Dataset accompanying the release of the Open MatSciML Toolkit, an open source software for development graph neural networks on the OpenCatalyst project using the Deep Graph Library (DGL). For more details about the Open MatSci ML Toolkit, check the associated open-source repository and paper. Compressed files ~8GB with uncompressed file being ~80 GB.
{"references": ["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., and Ulissi, Z. Open catalyst 2020 (oc20) dataset and community challenges. ACS Catalysis, 2021. doi: 10.1021/acscatal.0c04525."]}
Machine Learning, AI, OpenCatalyst Project, Materials Science, Deep Graph Library
Machine Learning, AI, OpenCatalyst Project, Materials Science, Deep Graph Library
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 18 |

Views provided by UsageCounts