Do Deep Neural Networks Learn Facial Action Units When Doing Expression Recognition? - Pooya Khorrami; Tom Le Paine; Thomas S. Huang (ICCV Workshops, 2015)

An Analysis of Unsupervised Pre-training in Light of Recent Advances. - Tom Le Paine; Pooya Khorrami; Wei Han 002; Thomas S. Huang (ICLR (Workshop), 2015)

How deep neural networks can improve emotion recognition on video data. - Pooya Khorrami; Tom Le Paine; Kevin Brady 001; Charlie K. Dagli; Thomas S. Huang (ICIP, 2016)

Seq-NMS for Video Object Detection. - Wei Han 002; Pooya Khorrami; Tom Le Paine; Prajit Ramachandran; Mohammad Babaeizadeh; Honghui Shi; Jianan Li 001; Shuicheng Yan; Thomas S. Huang (CoRR, 2016)

Fast Wavenet Generation Algorithm. - Tom Le Paine; Pooya Khorrami; Shiyu Chang; Yang Zhang 001; Prajit Ramachandran; Mark A. Hasegawa-Johnson; Thomas S. Huang (CoRR, 2016)

Fast Generation for Convolutional Autoregressive Models. - Prajit Ramachandran; Tom Le Paine; Pooya Khorrami; Mohammad Babaeizadeh; Shiyu Chang; Yang Zhang 001; Mark A. Hasegawa-Johnson; Roy H. Campbell; Thomas S. Huang (ICLR (Workshop), 2017)

Playing hard exploration games by watching YouTube. - Yusuf Aytar; Tobias Pfaff; David Budden; Tom Le Paine; Ziyu Wang 001; Nando de Freitas (NeurIPS, 2018)

One-Shot High-Fidelity Imitation: Training Large-Scale Deep Nets with RL. - Tom Le Paine; Sergio Gomez Colmenarejo; Ziyu Wang 001; Scott E. Reed; Yusuf Aytar; Tobias Pfaff; Matthew W. Hoffman; Gabriel Barth-Maron; Serkan Cabi; David Budden; Nando de Freitas (CoRR, 2018)

Improving the Gating Mechanism of Recurrent Neural Networks. - Albert Gu; Çaglar Gülçehre; Tom Le Paine; Matthew W. Hoffman; Razvan Pascanu (CoRR, 2019)

Grandmaster level in StarCraft II using multi-agent reinforcement learning. - Oriol Vinyals; Igor Babuschkin; Wojciech M. Czarnecki; Michaël Mathieu; Andrew Dudzik; Junyoung Chung; David H. Choi; Richard Powell; Timo Ewalds; Petko Georgiev; Junhyuk Oh; Dan Horgan; et al. (Nat., 2019)

Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. - Çaglar Gülçehre; Tom Le Paine; Bobak Shahriari; Misha Denil; Matt Hoffman 001; Hubert Soyer; Richard Tanburn; Steven Kapturowski; Neil C. Rabinowitz; Duncan Williams; Gabriel Barth-Maron; Ziyu Wang 001; et al. (ICLR, 2020)

Acme: A Research Framework for Distributed Reinforcement Learning. - Matt Hoffman 001; Bobak Shahriari; John Aslanides; Gabriel Barth-Maron; Feryal M. P. Behbahani; Tamara Norman; Abbas Abdolmaleki; Albin Cassirer; Fan Yang; Kate Baumli; Sarah Henderson; Alexander Novikov 001; et al. (CoRR, 2020)

RL Unplugged: Benchmarks for Offline Reinforcement Learning. - Çaglar Gülçehre; Ziyu Wang 001; Alexander Novikov 001; Tom Le Paine; Sergio Gómez Colmenarejo; Konrad Zolna; Rishabh Agarwal; Josh Merel; Daniel J. Mankowitz; Cosmin Paduraru; Gabriel Dulac-Arnold; Jerry Li; et al. (CoRR, 2020)

Hyperparameter Selection for Offline Reinforcement Learning. - Tom Le Paine; Cosmin Paduraru; Andrea Michi; Çaglar Gülçehre; Konrad Zolna; Alexander Novikov 001; Ziyu Wang 001; Nando de Freitas (CoRR, 2020)

Benchmarks for Deep Off-Policy Evaluation. - Justin Fu; Mohammad Norouzi 002; Ofir Nachum; George Tucker; Ziyu Wang 001; Alexander Novikov 001; Mengjiao Yang 001; Michael R. Zhang; Yutian Chen 001; Aviral Kumar; Cosmin Paduraru; Sergey Levine; et al. (ICLR, 2021)

Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization. - Michael R. Zhang; Tom Le Paine; Ofir Nachum; Cosmin Paduraru; George Tucker; Ziyu Wang 001; Mohammad Norouzi 002 (CoRR, 2021)

On Instrumental Variable Regression for Deep Offline Policy Evaluation. - Yutian Chen 001; Liyuan Xu; Çaglar Gülçehre; Tom Le Paine; Arthur Gretton; Nando de Freitas; Arnaud Doucet (J. Mach. Learn. Res., 2022)

π2vec: Policy Representations with Successor Features. - Gianluca Scarpellini; Ksenia Konyushkova; Claudio Fantacci; Tom Le Paine; Yutian Chen 001; Misha Denil (CoRR, 2023)

AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning. - Michaël Mathieu; Sherjil Ozair; Srivatsan Srinivasan; Çaglar Gülçehre; Shangtong Zhang; Ray Jiang; Tom Le Paine; Richard Powell; Konrad Zolna; Julian Schrittwieser; David H. Choi; Petko Georgiev; et al. (CoRR, 2023)

Reinforced Self-Training (ReST) for Language Modeling. - Çaglar Gülçehre; Tom Le Paine; Srivatsan Srinivasan; Ksenia Konyushkova; Lotte Weerts; Abhishek Sharma 015; Aditya Siddhant; Alex Ahern; Miaosen Wang; Chenjie Gu; Wolfgang Macherey; Arnaud Doucet; et al. (CoRR, 2023)