Veeriah, Vivek

11 publications

NeurIPS 2025 Generating Creative Chess Puzzles Xidong Feng, Vivek Veeriah, Marcus Chiam, Michael D Dennis, Federico Barbero, Johan Obando-Ceron, Jiaxin Shi, Satinder Singh, Shaobo Hou, Nenad Tomasev, Tom Zahavy

ICML 2023 ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs Ted Moskovitz, Brendan O’Donoghue, Vivek Veeriah, Sebastian Flennerhag, Satinder Singh, Tom Zahavy

NeurIPS 2021 Discovery of Options via Meta-Learned Subgoals Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado P van Hasselt, David Silver, Satinder P. Singh

NeurIPSW 2021 GrASP: Gradient-Based Affordance Selection for Planning Vivek Veeriah, Zeyu Zheng, Richard Lewis, Satinder Singh

NeurIPS 2021 Learning State Representations from Random Deep Action-Conditional Predictions Zeyu Zheng, Vivek Veeriah, Risto Vuorio, Richard L Lewis, Satinder P. Singh

NeurIPS 2020 A Self-Tuning Actor-Critic Algorithm Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado P van Hasselt, David Silver, Satinder P. Singh

AAAI 2020 How Should an Agent Practice? Janarthanan Rajendran, Richard L. Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh

NeurIPS 2020 Learning Retrospective Knowledge with Reverse Reinforcement Learning Shangtong Zhang, Vivek Veeriah, Shimon Whiteson

NeurIPS 2019 Discovery of Useful Questions as Auxiliary Tasks Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Janarthanan Rajendran, Richard L. Lewis, Junhyuk Oh, Hado P van Hasselt, David Silver, Satinder Singh

ECML-PKDD 2017 Crossprop: Learning Representations by Stochastic Meta-Gradient Descent in Neural Networks Vivek Veeriah, Shangtong Zhang, Richard S. Sutton

ICCV 2015 Differential Recurrent Neural Networks for Action Recognition Vivek Veeriah, Naifan Zhuang, Guo-Jun Qi