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David Brandfonbrener
David Brandfonbrener
Kempner Institute at Harvard University
Verified email at g.harvard.edu - Homepage
Title
Cited by
Cited by
Year
Frequentist regret bounds for randomized least-squares value iteration
A Zanette*, D Brandfonbrener*, E Brunskill, M Pirotta, A Lazaric
International Conference on Artificial Intelligence and Statistics, 1954-1964, 2020
1332020
Offline rl without off-policy evaluation
D Brandfonbrener, W Whitney, R Ranganath, J Bruna
Advances in neural information processing systems 34, 4933-4946, 2021
1192021
Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning
D Yarats*, D Brandfonbrener*, H Liu, M Laskin, P Abbeel, A Lazaric, ...
arXiv preprint arXiv:2201.13425, 2022
742022
When does return-conditioned supervised learning work for offline reinforcement learning?
D Brandfonbrener, A Bietti, J Buckman, R Laroche, J Bruna
Advances in Neural Information Processing Systems 35, 1542-1553, 2022
522022
Psychrnn: An accessible and flexible python package for training recurrent neural network models on cognitive tasks
DB Ehrlich, JT Stone, D Brandfonbrener, A Atanasov, JD Murray
eneuro 8 (1), 2021
242021
Evaluating representations by the complexity of learning low-loss predictors
WF Whitney, MJ Song, D Brandfonbrener, J Altosaar, K Cho
arXiv preprint arXiv:2009.07368, 2020
242020
Geometric insights into the convergence of nonlinear TD learning
D Brandfonbrener, J Bruna
International Conference on Learning Representations (ICLR), 2020
21*2020
Offline Contextual Bandits with Overparameterized Models
D Brandfonbrener, WF Whitney, R Ranganath, J Bruna
International Conference on Machine Learning (ICML), 2021, 2020
14*2020
Inverse dynamics pretraining learns good representations for multitask imitation
D Brandfonbrener, O Nachum, J Bruna
Advances in Neural Information Processing Systems 36, 2023
82023
Repeat after me: Transformers are better than state space models at copying
S Jelassi, D Brandfonbrener, SM Kakade, E Malach
arXiv preprint arXiv:2402.01032, 2024
52024
Visual backtracking teleoperation: A data collection protocol for offline image-based reinforcement learning
D Brandfonbrener, S Tu, A Singh, S Welker, C Boodoo, N Matni, J Varley
2023 IEEE International Conference on Robotics and Automation (ICRA), 11336 …, 2023
42023
Quantile filtered imitation learning
D Brandfonbrener, WF Whitney, R Ranganath, J Bruna
arXiv preprint arXiv:2112.00950, 2021
42021
Incorporating explicit uncertainty estimates into deep offline reinforcement learning
D Brandfonbrener, RT Combes, R Laroche
arXiv preprint arXiv:2206.01085, 2022
32022
Two-vertex generators of Jacobians of graphs
D Brandfonbrener, P Devlin, N Friedenberg, Y Ke, S Marcus, H Reichard, ...
The Electronic Journal of Combinatorics 25 (1), 2018
22018
Q-Probe: A Lightweight Approach to Reward Maximization for Language Models
K Li, S Jelassi, H Zhang, S Kakade, M Wattenberg, D Brandfonbrener
arXiv preprint arXiv:2402.14688, 2024
2024
Verified Multi-Step Synthesis using Large Language Models and Monte Carlo Tree Search
D Brandfonbrener, S Raja, T Prasad, C Loughridge, J Yang, S Henniger, ...
arXiv preprint arXiv:2402.08147, 2024
2024
Bridging the Gap from Supervised Learning to Control
D Brandfonbrener
New York University, 2023
2023
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