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Alexander Trott
Alexander Trott
MosaicML
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Cited by
Cited by
Year
The ai economist: Improving equality and productivity with ai-driven tax policies
S Zheng, A Trott, S Srinivasa, N Naik, M Gruesbeck, DC Parkes, R Socher
arXiv preprint arXiv:2004.13332, 2020
1562020
Explore, discover and learn: Unsupervised discovery of state-covering skills
V Campos, A Trott, C Xiong, R Socher, X Giró-i-Nieto, J Torres
International Conference on Machine Learning, 1317-1327, 2020
1252020
Keeping your distance: Solving sparse reward tasks using self-balancing shaped rewards
A Trott, S Zheng, C Xiong, R Socher
Advances in Neural Information Processing Systems 32, 2019
982019
Interpretable counting in visual question answering
AR Trott, C Xiong, R Socher
US Patent 10,592,767, 2020
902020
The AI Economist: Taxation policy design via two-level deep multiagent reinforcement learning
S Zheng, A Trott, S Srinivasa, DC Parkes, R Socher
Science advances 8 (18), eabk2607, 2022
762022
Interpretable counting for visual question answering
A Trott, C Xiong, R Socher
arXiv preprint arXiv:1712.08697, 2017
642017
Competitive experience replay
H Liu, A Trott, R Socher, C Xiong
arXiv preprint arXiv:1902.00528, 2019
602019
Song Choice Is Modulated by Female Movement in Drosophila Males
AR Trott, NC Donelson, LC Griffith, A Ejima
Public Library of Science 7 (9), e46025, 2012
322012
Input-gain control produces feature-specific surround suppression
AR Trott, RT Born
Journal of Neuroscience 35 (12), 4973-4982, 2015
312015
Cortical magnification plus cortical plasticity equals vision?
RT Born, AR Trott, TS Hartmann
Vision research 111, 161-169, 2015
302015
Learning world graphs to accelerate hierarchical reinforcement learning
W Shang, A Trott, S Zheng, C Xiong, R Socher
arXiv preprint arXiv:1907.00664, 2019
232019
Building a foundation for data-driven, interpretable, and robust policy design using the ai economist
A Trott, S Srinivasa, D van der Wal, S Haneuse, S Zheng
arXiv preprint arXiv:2108.02904, 2021
212021
The ai economist: Optimal economic policy design via two-level deep reinforcement learning
S Zheng, A Trott, S Srinivasa, DC Parkes, R Socher
arXiv preprint arXiv:2108.02755, 2021
212021
Learning world graphs to accelerate hierarchical reinforcement learning
W Shang, AR Trott, ST Zheng
US Patent 11,562,251, 2023
82023
Finding general equilibria in many-agent economic simulations using deep reinforcement learning
M Curry, AR Trott, S Phade, Y Bai, S Zheng
62021
Explore, discover and learn: unsupervised discovery of state-covering skills
V Campos Camúñez, A Trott, C Xiong, R Socher, X Giró Nieto, ...
ICML 2020, Thirty-seventh International Conference on Machine Learning …, 2020
62020
Platform behavior under market shocks: A simulation framework and reinforcement-learning based study
X Wang, GQ Ma, A Eden, C Li, A Trott, S Zheng, D Parkes
Proceedings of the ACM Web Conference 2023, 3592-3602, 2023
52023
Mosaicbert: How to train bert with a lunch money budget
J Portes, AR Trott, S Havens, D King, A Venigalla, M Nadeem, N Sardana, ...
Workshop on Efficient Systems for Foundation Models@ ICML2023, 2023
42023
LIMIT: Less Is More for Instruction Tuning Across Evaluation Paradigms
A Jha, S Havens, J Dohmann, A Trott, J Portes
arXiv preprint arXiv:2311.13133, 2023
32023
Modeling Bounded Rationality in Multi-Agent Simulations Using Rationally Inattentive Reinforcement Learning
T Mu, S Zheng, AR Trott
Transactions on Machine Learning Research, 2022
22022
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