Feryal M. P. Behbahani

33 papers A* 11Journal 18Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Training Language Models to Self-Correct via Reinforcement Learning. ICLR Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, Yi Su, John D. Co-Reyes, Avi Singh, Kate Baumli, Shariq Iqbal, Colton Bishop, Rebecca Roelofs, Lei M. Zhang, Kay McKinney, Disha Shrivastava, Cosmin Paduraru, George Tucker, Doina Precup, Feryal M. P. Behbahani, Aleksandra Faust
2024	A*	`conf`	Genie: Generative Interactive Environments. ICML Jake Bruce, Michael D. Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal M. P. Behbahani, Stephanie C. Y. Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott E. Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, Tim Rocktäschel
2024	J	`jnl`	Genie: Generative Interactive Environments. CoRR Jake Bruce, Michael Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal M. P. Behbahani, Stephanie Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott E. Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, Tim Rocktäschel
2024	A*	`conf`	Many-Shot In-Context Learning. NeurIPS Rishabh Agarwal, Avi Singh, Lei Zhang, Bernd Bohnet, Luis Rosias, Stephanie C. Y. Chan, Biao Zhang, Ankesh Anand, Zaheer Abbas, Azade Nova, John D. Co-Reyes, Eric Chu, Feryal M. P. Behbahani, Aleksandra Faust, Hugo Larochelle
2024	J	`jnl`	Many-Shot In-Context Learning. CoRR Rishabh Agarwal, Avi Singh, Lei M. Zhang, Bernd Bohnet, Stephanie Chan, Ankesh Anand, Zaheer Abbas, Azade Nova, John D. Co-Reyes, Eric Chu, Feryal M. P. Behbahani, Aleksandra Faust, Hugo Larochelle
2024	J	`jnl`	Open-Endedness is Essential for Artificial Superhuman Intelligence. CoRR Edward Hughes, Michael Dennis, Jack Parker-Holder, Feryal M. P. Behbahani, Aditi Mavalankar, Yuge Shi, Tom Schaul, Tim Rocktäschel
2024	A*	`conf`	Position: Open-Endedness is Essential for Artificial Superhuman Intelligence. ICML Edward Hughes, Michael D. Dennis, Jack Parker-Holder, Feryal M. P. Behbahani, Aditi Mavalankar, Yuge Shi, Tom Schaul, Tim Rocktäschel
2024	J	`jnl`	Training Language Models to Self-Correct via Reinforcement Learning. CoRR Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, Yi Su, John D. Co-Reyes, Avi Singh, Kate Baumli, Shariq Iqbal, Colton Bishop, Rebecca Roelofs, Lei M. Zhang, Kay McKinney, Disha Shrivastava, Cosmin Paduraru, George Tucker, Doina Precup, Feryal M. P. Behbahani, Aleksandra Faust
2023	A*	`conf`	Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality. ICLR Tom Zahavy, Yannick Schroecker, Feryal M. P. Behbahani, Kate Baumli, Sebastian Flennerhag, Shaobo Hou, Satinder Singh
2023	J	`jnl`	Hierarchical Reinforcement Learning in Complex 3D Environments. CoRR Bernardo Ávila Pires, Feryal M. P. Behbahani, Hubert Soyer, Kyriacos Nikiforou, Thomas Keck, Satinder Singh
2023	A*	`conf`	Human-Timescale Adaptation in an Open-Ended Task Space. ICML Jakob Bauer, Kate Baumli, Feryal M. P. Behbahani, Avishkar Bhoopchand, Nathalie Bradley-Schmieg, Michael Chang, Natalie Clay, Adrian Collister, Vibhavari Dasagi, Lucy Gonzalez, Karol Gregor, Edward Hughes, Sheleem Kashem, Maria Loks-Thompson, Hannah Openshaw, Jack Parker-Holder, Shreya Pathak, Nicolas Perez Nieves, Nemanja Rakicevic, Tim Rocktäschel, Yannick Schroecker, Satinder Singh, Jakub Sygnowski, Karl Tuyls, Sarah York, Alexander Zacherl, Lei M. Zhang
2023	J	`jnl`	Human-Timescale Adaptation in an Open-Ended Task Space. CoRR Adaptive Agent Team, Jakob Bauer, Kate Baumli, Satinder Baveja, Feryal M. P. Behbahani, Avishkar Bhoopchand, Nathalie Bradley-Schmieg, Michael Chang, Natalie Clay, Adrian Collister, Vibhavari Dasagi, Lucy Gonzalez, Karol Gregor, Edward Hughes, Sheleem Kashem, Maria Loks-Thompson, Hannah Openshaw, Jack Parker-Holder, Shreya Pathak, Nicolas Perez Nieves, Nemanja Rakicevic, Tim Rocktäschel, Yannick Schroecker, Jakub Sygnowski, Karl Tuyls, Sarah York, Alexander Zacherl, Lei Zhang
2023	A*	`conf`	Structured State Space Models for In-Context Reinforcement Learning. NeurIPS Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob N. Foerster, Satinder Singh, Feryal M. P. Behbahani
2023	J	`jnl`	Structured State Space Models for In-Context Reinforcement Learning. CoRR Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob N. Foerster, Satinder Singh, Feryal M. P. Behbahani
2023	J	`jnl`	Vision-Language Models as a Source of Rewards. CoRR Kate Baumli, Satinder Baveja, Feryal M. P. Behbahani, Harris Chan, Gheorghe Comanici, Sebastian Flennerhag, Maxime Gazeau, Kristian Holsheimer, Dan Horgan, Michael Laskin, Clare Lyle, Hussain Masoom, Kay McKinney, Volodymyr Mnih, Alexander Neitz, Fabio Pardo, Jack Parker-Holder, John Quan, Tim Rocktäschel, Himanshu Sahni, Tom Schaul, Yannick Schroecker, Stephen Spencer, Richie Steigerwald, Luyu Wang, Lei Zhang
2022	J	`jnl`	Analysing deep reinforcement learning agents trained with domain randomisation. Neurocomputing Tianhong Dai, Kai Arulkumaran, Tamara Gerbert, Samyakh Tukra, Feryal M. P. Behbahani, Anil Anthony Bharath
2022	J	`jnl`	Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality. CoRR Tom Zahavy, Yannick Schroecker, Feryal M. P. Behbahani, Kate Baumli, Sebastian Flennerhag, Shaobo Hou, Satinder Singh
2022	A*	`conf`	Model-Value Inconsistency as a Signal for Epistemic Uncertainty. ICML Angelos Filos, Eszter Vértes, Zita Marinho, Gregory Farquhar, Diana Borsa, Abram L. Friesen, Feryal M. P. Behbahani, Tom Schaul, André Barreto, Simon Osindero
2021	J	`jnl`	Model-Value Inconsistency as a Signal for Epistemic Uncertainty. CoRR Angelos Filos, Eszter Vértes, Zita Marinho, Gregory Farquhar, Diana Borsa, Abram L. Friesen, Feryal M. P. Behbahani, Tom Schaul, André Barreto, Simon Osindero
2021	A*	`conf`	On the role of planning in model-based deep reinforcement learning. ICLR Jessica B. Hamrick, Abram L. Friesen, Feryal M. P. Behbahani, Arthur Guez, Fabio Viola, Sims Witherspoon, Thomas Anthony, Lars Holger Buesing, Petar Velickovic, Theophane Weber
2020	J	`jnl`	Acme: A Research Framework for Distributed Reinforcement Learning. CoRR Matt Hoffman, 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, Sergio Gómez Colmenarejo, Serkan Cabi, Çaglar Gülçehre, Tom Le Paine, Andrew Cowie, Ziyu Wang, Bilal Piot, Nando de Freitas
2020	J	`jnl`	Learning Compositional Neural Programs for Continuous Control. CoRR Thomas Pierrot, Nicolas Perrin, Feryal M. P. Behbahani, Alexandre Laterre, Olivier Sigaud, Karim Beguir, Nando de Freitas
2020	A*	`conf`	Modular Meta-Learning with Shrinkage. NeurIPS Yutian Chen, Abram L. Friesen, Feryal M. P. Behbahani, Arnaud Doucet, David Budden, Matthew Hoffman, Nando de Freitas
2020	J	`jnl`	On the role of planning in model-based deep reinforcement learning. CoRR Jessica B. Hamrick, Abram L. Friesen, Feryal M. P. Behbahani, Arthur Guez, Fabio Viola, Sims Witherspoon, Thomas Anthony, Lars Buesing, Petar Velickovic, Théophane Weber
2020	J	`jnl`	Privileged Information Dropout in Reinforcement Learning. CoRR Pierre-Alexandre Kamienny, Kai Arulkumaran, Feryal M. P. Behbahani, Wendelin Boehmer, Shimon Whiteson
2019	J	`jnl`	Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation. CoRR Tianhong Dai, Kai Arulkumaran, Samyakh Tukra, Feryal M. P. Behbahani, Anil Anthony Bharath
2019	A*	`conf`	Learning From Demonstration in the Wild. ICRA Feryal M. P. Behbahani, Kyriacos Shiarlis, Xi Chen, Vitaly Kurin, Sudhanshu Kasewa, Ciprian Stirbu, João Gomes, Supratik Paul, Frans A. Oliehoek, João V. Messias, Shimon Whiteson
2019	J	`jnl`	Modular Meta-Learning with Shrinkage. CoRR Yutian Chen, Abram L. Friesen, Feryal M. P. Behbahani, David Budden, Matthew W. Hoffman, Arnaud Doucet, Nando de Freitas
2018	—	`conf`	Extending World Models for Multi-Agent Reinforcement Learning in MALMÖ. AIIDE Workshops Valliappa Chockalingam, Tegg Tae Kyong Sung, Feryal M. P. Behbahani, Rishab Gargeya, Amlesh Sivanantham, Aleksandra Malysheva
2018	J	`jnl`	Learning from Demonstration in the Wild. CoRR Feryal M. P. Behbahani, Kyriacos Shiarlis, Xi Chen, Vitaly Kurin, Sudhanshu Kasewa, Ciprian Stirbu, João Gomes, Supratik Paul, Frans A. Oliehoek, João V. Messias, Shimon Whiteson
2016	—	`conf`	Haptic SLAM: An Ideal Observer Model for Bayesian Inference of Object Shape and Hand Pose from Contact Dynamics. EuroHaptics (1) Feryal M. P. Behbahani, Guillem Singla-Buxarrais, A. Aldo Faisal
2016	—	`—`	Reverse-engineering the visual and haptic perceptual algorithms in the brain. Feryal M. P. Behbahani
2015	—	`conf`	Haptic SLAM for context-aware robotic hand prosthetics - simultaneous inference of hand pose and object shape using particle filters. NER Feryal M. P. Behbahani, Ruth Taunton, Andreas A. C. Thomik, A. Aldo Faisal