Daniel Freeman
Daniel Freeman
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Cited by
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
arXiv preprint arXiv:2206.04615, 2022
Topology and geometry of half-rectified network optimization
CD Freeman, J Bruna
arXiv preprint arXiv:1611.01540, 2016
Brax--a differentiable physics engine for large scale rigid body simulation
CD Freeman, E Frey, A Raichuk, S Girgin, I Mordatch, O Bachem
arXiv preprint arXiv:2106.13281, 2021
Multi-game decision transformers
KH Lee, O Nachum, MS Yang, L Lee, D Freeman, S Guadarrama, ...
Advances in Neural Information Processing Systems 35, 27921-27936, 2022
Modern approaches to exact diagonalization and selected configuration interaction with the adaptive sampling CI method
NM Tubman, CD Freeman, DS Levine, D Hait, M Head-Gordon, ...
Journal of chemical theory and computation 16 (4), 2139-2159, 2020
Understanding and correcting pathologies in the training of learned optimizers
L Metz, N Maheswaranathan, J Nixon, D Freeman, J Sohl-Dickstein
International Conference on Machine Learning, 4556-4565, 2019
Gradients are not all you need
L Metz, CD Freeman, SS Schoenholz, T Kachman
arXiv preprint arXiv:2111.05803, 2021
Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves
L Metz, N Maheswaranathan, CD Freeman, B Poole, J Sohl-Dickstein
arXiv preprint arXiv:2009.11243, 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
Learning to predict without looking ahead: World models without forward prediction
D Freeman, D Ha, L Metz
Advances in Neural Information Processing Systems 32, 2019
Using a thousand optimization tasks to learn hyperparameter search strategies
L Metz, N Maheswaranathan, R Sun, CD Freeman, B Poole, ...
arXiv preprint arXiv:2002.11887, 2020
A method for the determination of speed-dependent semi-classical vector correlations from sliced image anisotropies
MP Grubb, ML Warter, CD Freeman, NA West, KM Usakoski, KM Johnson, ...
The Journal of chemical physics 135 (9), 2011
Practical tradeoffs between memory, compute, and performance in learned optimizers
L Metz, CD Freeman, J Harrison, N Maheswaranathan, J Sohl-Dickstein
Conference on Lifelong Learning Agents, 142-164, 2022
Blocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learning
S Kamyar Seyed Ghasemipour, D Freeman, B David, SS Gu, S Kataoka, ...
arXiv e-prints, arXiv: 2203.13733, 2022
Relaxation dynamics of the toric code in contact with a thermal reservoir: Finite-size scaling in a low-temperature regime
CD Freeman, CM Herdman, DJ Gorman, KB Whaley
Physical Review B 90 (13), 134302, 2014
Barkour: Benchmarking animal-level agility with quadruped robots
K Caluwaerts, A Iscen, JC Kew, W Yu, T Zhang, D Freeman, KH Lee, ...
arXiv preprint arXiv:2305.14654, 2023
Engineering autonomous error correction in stabilizer codes at finite temperature
CD Freeman, CM Herdman, KB Whaley, 2016
Training learned optimizers with randomly initialized learned optimizers
L Metz, CD Freeman, N Maheswaranathan, J Sohl-Dickstein
arXiv preprint arXiv:2101.07367, 2021
Training optimizer neural networks
J Nixon, JN Sohl-Dickstein, LS Metz, CD Freeman, N Maheswaranathan
US Patent App. 16/586,220, 2020
Braxlines: Fast and interactive toolkit for rl-driven behavior engineering beyond reward maximization
SS Gu, M Diaz, DC Freeman, H Furuta, SKS Ghasemipour, A Raichuk, ...
arXiv preprint arXiv:2110.04686, 2021
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