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Johan S. Obando-Ceron
Johan Samir Obando-Ceron – Johan Samir Obando Ceron
Person information
- affiliation: University of Montréal, Mila, Canada
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2020 – today
- 2026
- [i35]Ali Saheb Pasand, Johan S. Obando-Ceron, Aaron C. Courville, Pouya Bashivan, Pablo Samuel Castro:
Stable Deep Reinforcement Learning via Isotropic Gaussian Representations. CoRR abs/2602.19373 (2026) - [i34]Hugh Blayney, Alvaro Arroyo, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Michael M. Bronstein, Xiaowen Dong:
A Mechanistic Analysis of Looped Reasoning Language Models. CoRR abs/2604.11791 (2026) - [i33]Jishnu Sethumadhavan Nair, Patrice Béchard, Rishabh Maheshwary, Surajit Dasgupta, Sravan Ramachandran, Aakash Bhagat
, Shruthan Radhakrishna, Pulkit Pattnaik, Johan S. Obando-Ceron, Shiva Krishna Reddy Malay, Sagar Davasam, Seganrasan Subramanian, Vipul Mittal, Sridhar Krishna Nemala, Christopher Pal, Srinivas Sunkara, Sai Rajeswar:
Do Enterprise Systems Need Learned World Models? The Importance of Context to Infer Dynamics. CoRR abs/2605.12178 (2026) - [i32]Bingxu Liu, Jiashun Liu, Johan S. Obando-Ceron, Hao Wang, Runze Liu, Pablo Samuel Castro, Aaron C. Courville, Ling Pan:
Local Guidance, Global Impact: Gaussian-Reshaped Trust Region Unlocks Behavior Transitions. CoRR abs/2606.03382 (2026) - [i31]Johan S. Obando-Ceron, Lu Li, Scott Fujimoto, Pierre-Luc Bacon, Aaron C. Courville, Pablo Samuel Castro:
Representation Learning Enables Scalable Multitask Deep Reinforcement Learning. CoRR abs/2606.05555 (2026) - 2025
- [c18]Ashmal Vayani, Dinura Dissanayake, Hasindri Watawana, Noor Ahsan, Nevasini Sasikumar, Omkar Thawakar, Henok Biadglign Ademtew, Yahya Hmaiti, Amandeep Kumar, Kartik Kuckreja, Mykola Maslych, Wafa Al Ghallabi, Mihail Minkov Mihaylov, Chao Qin, Abdelrahman M. Shaker, Mike Zhang
All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages. CVPR 2025: 19565-19575 - [c17]Jiashun Liu, Johan S. Obando-Ceron, Aaron C. Courville, Ling Pan:
Neuroplastic Expansion in Deep Reinforcement Learning. ICLR 2025 - [c16]Angelika Romanou, Negar Foroutan, Anna Sotnikova, Zeming Chen, Sree Harsha Nelaturu, Shivalika Singh, Rishabh Maheshwary, Micol Altomare, Mohamed A. Haggag, Imanol Schlag, Marzieh Fadaee, Sara Hooker, Antoine Bosselut, Snegha A, Alfonso Amayuelas, Azril Hafizi Amirudin, Viraat Aryabumi, Danylo Boiko, Michael Chang, Jenny Chim, Gal Cohen, Aditya Kumar Dalmia, Abraham Diress, Sharad Duwal, Daniil Dzenhaliou, Daniel Fernando Erazo Florez, Fabian Farestam, Joseph Marvin Imperial, Shayekh Bin Islam, Perttu Isotalo, Maral Jabbarishiviari, Börje F. Karlsson, Eldar Khalilov, Christopher Klamm, Fajri Koto, Dominik Krzeminski, Gabriel Adriano de Melo, Syrielle Montariol, Yiyang Nan, Joel Niklaus, Jekaterina Novikova, Johan Samir Obando-Ceron, Debjit Paul, Esther Ploeger, Jebish Purbey, Swati Rajwal, Selvan Sunitha Ravi, Sara Rydell, Roshan Santhosh, Drishti Sharma, Marjana Prifti Skenduli, Arshia Soltani Moakhar, Bardia Soltani Moakhar, Ran Tamir, Ayush Kumar Tarun, Azmine Toushik Wasi, Thenuka Ovin Weerasinghe, Serhan Yilmaz, Mike Zhang:
INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge. ICLR 2025 - [c15]Ghada Sokar, Johan S. Obando-Ceron, Aaron C. Courville, Hugo Larochelle, Pablo Samuel Castro:
Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL. ICLR 2025 - [c14]Jiashun Liu, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Ling Pan:
The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning. ICML 2025 - [c13]Walter Mayor, Johan S. Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro:
The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks. ICML 2025 - [c12]Hongyao Tang, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Glen Berseth:
Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn. ICML 2025 - [c11]Brian R. Bartoldson, Siddarth Venkatraman, James Diffenderfer, Moksh Jain, Tal Ben-Nun, Seanie Lee, Minsu Kim, Johan S. Obando-Ceron, Yoshua Bengio, Bhavya Kailkhura:
Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training. NeurIPS 2025 - [c10]Roger Creus Castanyer, Johan S. Obando-Ceron, Lu Li, Pierre-Luc Bacon, Glen Berseth, Aaron C. Courville, Pablo Samuel Castro:
Stable Gradients for Stable Learning at Scale in Deep Reinforcement Learning. NeurIPS 2025 - [c9]Xidong Feng, Vivek Veeriah, Marcus Chiam, Michael Dennis, Federico Barbero, Johan S. Obando-Ceron, Jiaxin Shi, Satinder P. Singh, Shaobo Hou, Nenad Tomasev, Tom Zahavy:
Generating Creative Chess Puzzles. NeurIPS 2025 - [c8]Jiashun Liu, Zihao Wu, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Ling Pan:
Measure gradients, not activations! Enhancing neuronal activity in deep reinforcement learning. NeurIPS 2025 - [i30]Brian R. Bartoldson, Siddarth Venkatraman, James Diffenderfer, Moksh Jain, Tal Ben-Nun, Seanie Lee, Minsu Kim, Johan S. Obando-Ceron, Yoshua Bengio, Bhavya Kailkhura
Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training. CoRR abs/2503.18929 (2025) - [i29]Zhixuan Lin, Johan S. Obando-Ceron, Xu Owen He, Aaron C. Courville:
Adaptive Computation Pruning for the Forgetting Transformer. CoRR abs/2504.06949 (2025) - [i28]Israfel Salazar, Manuel Fernández Burda, Shayekh Bin Islam, Arshia Soltani Moakhar, Shivalika Singh, Fabian Farestam, Angelika Romanou, Danylo Boiko
Kaleidoscope: In-language Exams for Massively Multilingual Vision Evaluation. CoRR abs/2504.07072 (2025) - [i27]Jiashun Liu, Zihao Wu, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Ling Pan:
Measure gradients, not activations! Enhancing neuronal activity in deep reinforcement learning. CoRR abs/2505.24061 (2025) - [i26]Hongyao Tang, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Glen Berseth:
Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn. CoRR abs/2506.00592 (2025) - [i25]Walter Mayor, Johan S. Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro:
The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks. CoRR abs/2506.03404 (2025) - [i24]Jiashun Liu, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Ling Pan:
The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning. CoRR abs/2506.13672 (2025) - [i23]Roger Creus Castanyer, Johan S. Obando-Ceron, Lu Li, Pierre-Luc Bacon
Stable Gradients for Stable Learning at Scale in Deep Reinforcement Learning. CoRR abs/2506.15544 (2025) - [i22]Siddarth Venkatraman, Vineet Jain, Sarthak Mittal, Vedant Shah, Johan S. Obando-Ceron, Yoshua Bengio, Brian R. Bartoldson, Bhavya Kailkhura, Guillaume Lajoie, Glen Berseth, Nikolay Malkin, Moksh Jain:
Recursive Self-Aggregation Unlocks Deep Thinking in Large Language Models. CoRR abs/2509.26626 (2025) - [i21]Jiashun Liu, Johan S. Obando-Ceron, Han Lu, Yancheng He, Weixun Wang, Wenbo Su, Bo Zheng, Pablo Samuel Castro, Aaron C. Courville, Ling Pan:
Asymmetric Proximal Policy Optimization: mini-critics boost LLM reasoning. CoRR abs/2510.01656 (2025) - [i20]Johan S. Obando-Ceron, Walter Mayor, Samuel Lavoie, Scott Fujimoto, Aaron C. Courville, Pablo Samuel Castro:
Simplicial Embeddings Improve Sample Efficiency in Actor-Critic Agents. CoRR abs/2510.13704 (2025) - [i19]Vivek Veeriah, Federico Barbero, Marcus Chiam, Xidong Feng, Michael Dennis, Ryan Pachauri, Thomas Tumiel, Johan S. Obando-Ceron, Jiaxin Shi, Shaobo Hou, Satinder Singh, Nenad Tomasev, Tom Zahavy:
Evaluating In Silico Creativity: An Expert Review of AI Chess Compositions. CoRR abs/2510.23772 (2025) - [i18]Xidong Feng, Vivek Veeriah, Marcus Chiam, Michael Dennis, Ryan Pachauri, Thomas Tumiel, Federico Barbero, Johan S. Obando-Ceron, Jiaxin Shi, Satinder Singh, Shaobo Hou, Nenad Tomasev, Tom Zahavy:
Generating Creative Chess Puzzles. CoRR abs/2510.23881 (2025) - [i17]Aarash Feizi, Shravan Nayak, Xiangru Jian, Kevin Qinghong Lin, Kaixin Li, Rabiul Awal, Xing Han Lù, Johan S. Obando-Ceron, Juan A. Rodríguez, Nicolas Chapados, David Vázquez, Adriana Romero-Soriano, Reihaneh Rabbany, Perouz Taslakian, Christopher Pal, Spandana Gella, Sai Rajeswar:
Grounding Computer Use Agents on Human Demonstrations. CoRR abs/2511.07332 (2025) - [i16]Vedant Shah, Johan S. Obando-Ceron, Vineet Jain, Brian R. Bartoldson, Bhavya Kailkhura, Sarthak Mittal, Glen Berseth, Pablo Samuel Castro, Yoshua Bengio, Nikolay Malkin, Moksh Jain, Siddarth Venkatraman, Aaron C. Courville:
A Comedy of Estimators: On KL Regularization in RL Training of LLMs. CoRR abs/2512.21852 (2025) - 2024
- [j2]Johan S. Obando-Ceron, João Guilherme Madeira Araújo, Aaron C. Courville, Pablo Samuel Castro:
On the consistency of hyper-parameter selection in value-based deep reinforcement learning. RLJ 3: 1037-1059 (2024) - [j1]Timon Willi, Johan S. Obando-Ceron, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Pablo Samuel Castro:
Mixture of Experts in a Mixture of RL settings. RLJ 3: 1072-1105 (2024) - [c7]Joo Hyung Lee, Wonpyo Park, Nicole Mitchell, Jonathan Pilault, Johan Samir Obando Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Woohyun Han, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart J. C. Bik, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann N. Dauphin, Gintare Karolina Dziugaite, Pablo Samuel Castro, Utku Evci:
Jaxpruner: A Concise Library for Sparsity Research. CPAL 2024: 515-528 - [c6]Johan S. Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro:
In value-based deep reinforcement learning, a pruned network is a good network. ICML 2024: 38495-38519 - [c5]Johan S. Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro:
Mixtures of Experts Unlock Parameter Scaling for Deep RL. ICML 2024: 38520-38540 - [i15]Johan S. Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob N. Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro:
Mixtures of Experts Unlock Parameter Scaling for Deep RL. CoRR abs/2402.08609 (2024) - [i14]Johan S. Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro:
In deep reinforcement learning, a pruned network is a good network. CoRR abs/2402.12479 (2024) - [i13]Johan S. Obando-Ceron, João G. M. Araújo, Aaron C. Courville, Pablo Samuel Castro:
On the consistency of hyper-parameter selection in value-based deep reinforcement learning. CoRR abs/2406.17523 (2024) - [i12]Timon Willi, Johan S. Obando-Ceron, Jakob N. Foerster, Karolina Dziugaite, Pablo Samuel Castro:
Mixture of Experts in a Mixture of RL settings. CoRR abs/2406.18420 (2024) - [i11]Ghada Sokar, Johan S. Obando-Ceron, Aaron C. Courville, Hugo Larochelle, Pablo Samuel Castro:
Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL. CoRR abs/2410.01930 (2024) - [i10]Jiashun Liu, Johan S. Obando-Ceron, Aaron C. Courville, Ling Pan:
Neuroplastic Expansion in Deep Reinforcement Learning. CoRR abs/2410.07994 (2024) - [i9]Ashmal Vayani, Dinura Dissanayake, Hasindri Watawana
All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages. CoRR abs/2411.16508 (2024) - [i8]Angelika Romanou, Negar Foroutan, Anna Sotnikova, Zeming Chen
INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge. CoRR abs/2411.19799 (2024) - 2023
- [c4]Johan S. Obando-Ceron, Marc G. Bellemare, Pablo Samuel Castro:
The Small Batch Size Anomaly in Multistep Deep Reinforcement Learning. Tiny Papers @ ICLR 2023 - [c3]Max Schwarzer, Johan S. Obando-Ceron, Aaron C. Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro:
Bigger, Better, Faster: Human-level Atari with human-level efficiency. ICML 2023: 30365-30380 - [c2]Johan S. Obando-Ceron, Marc G. Bellemare, Pablo Samuel Castro:
Small batch deep reinforcement learning. NeurIPS 2023 - [i7]Joo Hyung Lee, Wonpyo Park, Nicole Mitchell, Jonathan Pilault, Johan S. Obando-Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart J. C. Bik, Woohyun Han, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann N. Dauphin, Karolina Dziugaite, Pablo Samuel Castro, Utku Evci:
JaxPruner: A concise library for sparsity research. CoRR abs/2304.14082 (2023) - [i6]Max Schwarzer, Johan S. Obando-Ceron, Aaron C. Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro:
Bigger, Better, Faster: Human-level Atari with human-level efficiency. CoRR abs/2305.19452 (2023) - [i5]Johan S. Obando-Ceron, Victor Romero-Cano, Sildomar Monteiro:
Probabilistic Multimodal Depth Estimation Based on Camera-LiDAR Sensor Fusion. CoRR abs/2307.10519 (2023) - [i4]Johan S. Obando-Ceron, Marc G. Bellemare, Pablo Samuel Castro:
Small batch deep reinforcement learning. CoRR abs/2310.03882 (2023) - 2021
- [c1]Johan S. Obando-Ceron, Pablo Samuel Castro:
Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research. ICML 2021: 1373-1383 - 2020
- [i3]Johan S. Obando-Ceron, Pablo Samuel Castro:
Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research. CoRR abs/2011.14826 (2020)
2010 – 2019
- 2019
- [i2]Johan S. Obando-Ceron, Victor Romero-Cano, Walter Mayor Toro:
Exploiting the potential of deep reinforcement learning for classification tasks in high-dimensional and unstructured data. CoRR abs/1912.09595 (2019) - [i1]Walter M. Mayor Toro, Juan Carlos Perafan Villota, Oscar H. Mondragon, Johan S. Obando-Ceron:
Divide and Conquer: an Accurate Machine Learning Algorithm to Process Split Videos on a Parallel Processing Infrastructure. CoRR abs/1912.09601 (2019)
Coauthor Index
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last updated on 2026-08-18 00:02 CEST by the dblp team
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