Sotabase

Career

· Co-founder, manifest ai2023–
· PhD Candidate (Mila), McGill University2018–
· AI Resident, Google Brain2017–2018
· M.S. in Language Technologies, Carnegie Mellon University2016–2017
· Research Intern, Microsoft Research2016–2016
· Member Educator, Sigma Alpha Epsilon2014–
· B.S. in Computer Science (Minor Philosophy), Carnegie Mellon University2013–2017

Publications (22)

Thermometer Encoding: One Hot Way To Resist Adversarial Examples
International Conference on Learning Representations · 2018
639
cited
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion
Neural Information Processing Systems · 2018
354
cited
DeepMDP: Learning Continuous Latent Space Models for Representation Learning
International Conference on Machine Learning · 2019
324
cited
The Importance of Pessimism in Fixed-Dataset Policy Optimization
International Conference on Learning Representations · 2020
143
cited
Is Generator Conditioning Causally Related to GAN Performance?
International Conference on Machine Learning · 2018
121
cited
When does return-conditioned supervised learning work for offline reinforcement learning?
Neural Information Processing Systems · 2022
86
cited
Neural Lattice Language Models
Transactions of the Association for Computational Linguistics · 2018
30
cited
Transition-Based Dependency Parsing with Heuristic Backtracking
Conference on Empirical Methods in Natural Language Processing · 2016
10
cited
Neural Regression For Scale-Varying Targets
2022
3
cited
Non-Markovian policies occupancy measures
arXiv.org · 2022
1
cited
Deep Autoregressive Regression
arXiv.org · 2022
Sotabase
Jacob Buckman | Researcher Profile | Sotabase | Sotabase