Dataset Groups Activity Stream OC2022 The dataset used for training scalable graph foundation models (GFM) for atomistic materials modeling. BibTex: @dataset{Massimiliano_Lupo_Pasini_and_Jong_Youl_Choi_and_Kshitij_Mehta_and_Pei_Zhang_and_David_Rogers_and_Jonghyun_Bae_and_Khaled_Z_Ibrahim_and_Ashwin_M_Aji_and_Karl_W_Schulz_and_Jord`a_Polo_2024, abstract = {The dataset used for training scalable graph foundation models (GFM) for atomistic materials modeling.}, author = {Massimiliano Lupo Pasini and Jong Youl Choi and Kshitij Mehta and Pei Zhang and David Rogers and Jonghyun Bae and Khaled Z. Ibrahim and Ashwin M. Aji and Karl W. Schulz and Jord`a Polo}, doi = {10.57702/ibdgmcbk}, institution = {No Organization}, keyword = {'atomistic materials modeling', 'graph foundation models', 'scalable training'}, month = {dec}, publisher = {TIB}, title = {OC2022}, url = {https://service.tib.eu/ldmservice/dataset/oc2022}, year = {2024} }
