no code implementations • 18 Oct 2023 • Mengjiao Yang, KwangHwan Cho, Amil Merchant, Pieter Abbeel, Dale Schuurmans, Igor Mordatch, Ekin Dogus Cubuk
Lastly, we show that conditional generation with UniMat can scale to previously established crystal datasets with up to millions of crystals structures, outperforming random structure search (the current leading method for structure discovery) in discovering new stable materials.
no code implementations • 2 Oct 2023 • Muratahan Aykol, Amil Merchant, Simon Batzner, Jennifer N. Wei, Ekin Dogus Cubuk
Crystallization of the amorphous phases into metastable crystals plays a fundamental role in the formation of new matter, from geological to biological processes in nature to synthesis and development of new materials in the laboratory.
1 code implementation • 17 Nov 2022 • Luke Metz, James Harrison, C. Daniel Freeman, Amil Merchant, Lucas Beyer, James Bradbury, Naman Agrawal, Ben Poole, Igor Mordatch, Adam Roberts, Jascha Sohl-Dickstein
While deep learning models have replaced hand-designed features across many domains, these models are still trained with hand-designed optimizers.
no code implementations • 20 Jul 2021 • Amil Merchant, Luke Metz, Sam Schoenholz, Ekin Dogus Cubuk
Optimization of non-convex loss surfaces containing many local minima remains a critical problem in a variety of domains, including operations research, informatics, and material design.
no code implementations • 15 Oct 2020 • Amil Merchant, Barret Zoph, Ekin Dogus Cubuk
Data augmentation has emerged as a powerful technique for improving the performance of deep neural networks and led to state-of-the-art results in computer vision.
no code implementations • EMNLP (BlackboxNLP) 2020 • Amil Merchant, Elahe Rahimtoroghi, Ellie Pavlick, Ian Tenney
While there has been much recent work studying how linguistic information is encoded in pre-trained sentence representations, comparatively little is understood about how these models change when adapted to solve downstream tasks.