Amil Merchant
Amil Merchant
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Cited by
Cited by
Scaling deep learning for materials discovery
A Merchant, S Batzner, SS Schoenholz, M Aykol, G Cheon, ED Cubuk
Nature 624 (7990), 80-85, 2023
What happens to BERT embeddings during fine-tuning?
A Merchant, E Rahimtoroghi, E Pavlick, I Tenney
arXiv preprint arXiv:2004.14448, 2020
An autonomous laboratory for the accelerated synthesis of novel materials
NJ Szymanski, B Rendy, Y Fei, RE Kumar, T He, D Milsted, MJ McDermott, ...
Nature 624 (7990), 86-91, 2023
Velo: Training versatile learned optimizers by scaling up
L Metz, J Harrison, CD Freeman, A Merchant, L Beyer, J Bradbury, ...
arXiv preprint arXiv:2211.09760, 2022
Constitutional dimensions of predictive algorithms in criminal justice
M Brenner, JS Gersen, M Haley, M Lin, A Merchant, RJ Millett, SK Sarkar, ...
Harv. CR-CLL Rev. 55, 267, 2020
Scalable diffusion for materials generation
M Yang, KH Cho, A Merchant, P Abbeel, D Schuurmans, I Mordatch, ...
arXiv preprint arXiv:2311.09235, 2023
Learn2hop: Learned optimization on rough landscapes
A Merchant, L Metz, SS Schoenholz, ED Cubuk
International Conference on Machine Learning, 7643-7653, 2021
Does data augmentation benefit from split batchnorms
A Merchant, B Zoph, ED Cubuk
arXiv preprint arXiv:2010.07810, 2020
Universal Causal Evaluation Engine: An API for empirically evaluating causal inference models
A Lin, A Merchant, SK Sarkar, A D’Amour
The 2019 ACM SIGKDD Workshop on Causal Discovery, 50-58, 2019
Accurate prediction of experimental band gaps from large language model-based data extraction
SJ Yang, S Li, S Venugopalan, V Tshitoyan, M Aykol, A Merchant, ...
arXiv preprint arXiv:2311.13778, 2023
Predicting emergence of crystals from amorphous matter with deep learning
M Aykol, A Merchant, S Batzner, JN Wei, ED Cubuk
arXiv preprint arXiv:2310.01117, 2023
Predicting Properties of Amorphous Solids with Graph Network Potentials
M Aykol, JN Wei, S Batzner, A Merchant, ED Cubuk
1st Workshop on the Synergy of Scientific and Machine Learning Modeling …, 2023
Optimization using learned neural network optimizers
ED Cubuk, LS Metz, SS Schoenholz, AA Merchant
US Patent App. 17/665,457, 2022
Strided Transformers for Partially-Parallelized Inference
A Merchant, ED Cubuk, S Ermon
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