| Scaling deep learning for materials discovery A Merchant, S Batzner, SS Schoenholz, M Aykol, G Cheon, ED Cubuk Nature 624 (7990), 80-85, 2023 | 638 | 2023 |
| 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 | 324 | 2023 |
| What happens to BERT embeddings during fine-tuning? A Merchant, E Rahimtoroghi, E Pavlick, I Tenney arXiv preprint arXiv:2004.14448, 2020 | 212 | 2020 |
| 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 | 72 | 2022 |
| Scalable diffusion for materials generation S Yang, KH Cho, A Merchant, P Abbeel, D Schuurmans, I Mordatch, ... arXiv preprint arXiv:2311.09235, 2023 | 39 | 2023 |
| 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 | 36 | 2020 |
| Learn2hop: Learned optimization on rough landscapes A Merchant, L Metz, SS Schoenholz, ED Cubuk International Conference on Machine Learning, 7643-7653, 2021 | 16 | 2021 |
| Does data augmentation benefit from split batchnorms A Merchant, B Zoph, ED Cubuk arXiv preprint arXiv:2010.07810, 2020 | 12 | 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 | 7 | 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 | 6 | 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 | 5 | 2023 |
| Self-refining diffusion samplers: Enabling parallelization via parareal iterations N Selvam, A Merchant, S Ermon Advances in Neural Information Processing Systems 37, 5429-5453, 2025 | 2 | 2025 |
| 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 | 2 | 2023 |
| Optimization using learned neural network optimizers ED Cubuk, LS Metz, SS Schoenholz, AA Merchant US Patent App. 17/665,457, 2022 | 1 | 2022 |
| Predicting emergence of crystals from amorphous precursors with deep learning potentials M Aykol, A Merchant, S Batzner, JN Wei, ED Cubuk Nature Computational Science, 1-7, 2024 | | 2024 |
| Self-Refining Diffusion Samplers: Enabling Parallelization via Parareal Iterations N Roashan Selvam, A Merchant, S Ermon arXiv e-prints, arXiv: 2412.08292, 2024 | | 2024 |
| Efficient Exploratory Synthesis of Quaternary Cesium Chlorides Guided by In Silico Predictions A Miura, M Aykol, S Kozaki, C Moriyoshi, S Kobayashi, S Kawaguchi, ... Journal of the American Chemical Society 146 (43), 29637-29644, 2024 | | 2024 |
| Learn2Hop: Learned Optimization on Rough Landscapes With Applications to Atomic Structural Optimization A Merchant, L Metz, S Schoenholz, ED Cubuk | | |
| Strided Transformers for Partially-Parallelized Inference A Merchant, ED Cubuk, S Ermon | | |
