Johan S. Obando-Ceron

41 papers A* 11Journal 29Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Stable Deep Reinforcement Learning via Isotropic Gaussian Representations. CoRR Ali Saheb Pasand, Johan S. Obando-Ceron, Aaron C. Courville, Pouya Bashivan, Pablo Samuel Castro
2025	J	`jnl`	A Comedy of Estimators: On KL Regularization in RL Training of LLMs. CoRR 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
2025	J	`jnl`	Adaptive Computation Pruning for the Forgetting Transformer. CoRR Zhixuan Lin, Johan S. Obando-Ceron, Xu Owen He, Aaron C. Courville
2025	A*	`conf`	All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages. CVPR 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, Mahardika Krisna Ihsani, Amiel Gian Esplana, Monil Gokani, Shachar Mirkin, Harsh Singh, Ashay Srivastava, Endre Hamerlik, Fathinah Asma Izzati, Fadillah Adamsyah Maani, Sebastian Cavada, Jenny Chim, Rohit Gupta, Sanjay Manjunath, Kamila Zhumakhanova, Feno Heriniaina Rabevohitra, Azril Hafizi Amirudin, Muhammad Ridzuan, Daniya Najiha Abdul Kareem, Ketan Pravin More, Kunyang Li, Pramesh Shakya, Muhammad Saad, Amirpouya Ghasemaghaei, Amirbek Djanibekov, Dilshod Azizov, Branislava Jankovic, Naman Bhatia, Alvaro Cabrera, Johan S. Obando-Ceron, Olympiah Otieno, Fabian Farestam, Muztoba Rabbani, Sanoojan Baliah, Santosh Sanjeev, Abduragim Shtanchaev, Maheen Fatima, Thao Nguyen, Amrin Kareem, Toluwani Aremu, Nathan Augusto Zacarias Xavier, Amit Bhatkal, Hawau Olamide Toyin, Aman Chadha, Hisham Cholakkal, Rao Muhammad Anwer, Michael Felsberg, Jorma Laaksonen, Thamar Solorio, Monojit Choudhury, Ivan Laptev, Mubarak Shah, Salman H. Khan, Fahad Shahbaz Khan
2025	J	`jnl`	Asymmetric Proximal Policy Optimization: mini-critics boost LLM reasoning. CoRR Jiashun Liu, Johan S. Obando-Ceron, Han Lu, Yancheng He, Weixun Wang, Wenbo Su, Bo Zheng, Pablo Samuel Castro, Aaron C. Courville, Ling Pan
2025	A*	`conf`	Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL. ICLR Ghada Sokar, Johan S. Obando-Ceron, Aaron C. Courville, Hugo Larochelle, Pablo Samuel Castro
2025	J	`jnl`	Kaleidoscope: In-language Exams for Massively Multilingual Vision Evaluation. CoRR Israfel Salazar, Manuel Fernández Burda, Shayekh Bin Islam, Arshia Soltani Moakhar, Shivalika Singh, Fabian Farestam, Angelika Romanou, Danylo Boiko, Dipika Khullar, Mike Zhang, Dominik Krzeminski, Jekaterina Novikova, Luísa Shimabucoro, Joseph Marvin Imperial, Rishabh Maheshwary, Sharad Duwal, Alfonso Amayuelas, Swati Rajwal, Jebish Purbey, Ahmed Ruby, Nicholas Popovic, Marek Suppa, Azmine Toushik Wasi, Ram Mohan Rao Kadiyala, Olga Tsymboi, Maksim Kostritsya, Bardia Soltani Moakhar, Gabriel da Costa Merlin, Otávio Ferracioli Coletti, Maral Jabbarishiviari, MohammadAmin farahani fard, Silvia Fernandez, María Grandury, Dmitry Abulkhanov, Drishti Sharma, André Guarnier de Mitri, Leticia Bossatto Marchezi, Setayesh Heydari, Johan S. Obando-Ceron, Nazar Kohut, Beyza Ermis, Desmond Elliott, Enzo Ferrante, Sara Hooker, Marzieh Fadaee
2025	J	`jnl`	Measure gradients, not activations! Enhancing neuronal activity in deep reinforcement learning. CoRR Jiashun Liu, Zihao Wu, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Ling Pan
2025	A*	`conf`	Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn. ICML Hongyao Tang, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Glen Berseth
2025	J	`jnl`	Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn. CoRR Hongyao Tang, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Glen Berseth
2025	A*	`conf`	Neuroplastic Expansion in Deep Reinforcement Learning. ICLR Jiashun Liu, Johan S. Obando-Ceron, Aaron C. Courville, Ling Pan
2025	J	`jnl`	Recursive Self-Aggregation Unlocks Deep Thinking in Large Language Models. CoRR 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
2025	J	`jnl`	Simplicial Embeddings Improve Sample Efficiency in Actor-Critic Agents. CoRR Johan S. Obando-Ceron, Walter Mayor, Samuel Lavoie, Scott Fujimoto, Aaron C. Courville, Pablo Samuel Castro
2025	J	`jnl`	Stable Gradients for Stable Learning at Scale in Deep Reinforcement Learning. CoRR Roger Creus Castanyer, Johan S. Obando-Ceron, Lu Li, Pierre-Luc Bacon, Glen Berseth, Aaron C. Courville, Pablo Samuel Castro
2025	A*	`conf`	The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning. ICML Jiashun Liu, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Ling Pan
2025	J	`jnl`	The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning. CoRR Jiashun Liu, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Ling Pan
2025	A*	`conf`	The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks. ICML Walter Mayor, Johan S. Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro
2025	J	`jnl`	The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks. CoRR Walter Mayor, Johan S. Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro
2025	J	`jnl`	Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training. CoRR Brian R. Bartoldson, Siddarth Venkatraman, James Diffenderfer, Moksh Jain, Tal Ben-Nun, Seanie Lee, Minsu Kim, Johan S. Obando-Ceron, Yoshua Bengio, Bhavya Kailkhura
2024	J	`jnl`	All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages. CoRR 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 Mihaylov, Chao Qin, Abdelrahman M. Shaker, Mike Zhang, Mahardika Krisna Ihsani, Amiel Esplana, Monil Gokani, Shachar Mirkin, Harsh Singh, Ashay Srivastava, Endre Hamerlik, Fathinah Asma Izzati, Fadillah Adamsyah Maani, Sebastian Cavada, Jenny Chim, Rohit Gupta, Sanjay Manjunath, Kamila Zhumakhanova, Feno Heriniaina Rabevohitra, Azril Amirudin, Muhammad Ridzuan, Daniya Kareem, Ketan More, Kunyang Li, Pramesh Shakya, Muhammad Saad, Amirpouya Ghasemaghaei, Amirbek Djanibekov, Dilshod Azizov, Branislava Jankovic, Naman Bhatia, Alvaro Cabrera, Johan S. Obando-Ceron, Olympiah Otieno, Fabian Farestam, Muztoba Rabbani, Sanoojan Baliah, Santosh Sanjeev, Abduragim Shtanchaev, Maheen Fatima, Thao Nguyen, Amrin Kareem, Toluwani Aremu, Nathan A. Z. Xavier, Amit Bhatkal, Hawau Olamide Toyin, Aman Chadha, Hisham Cholakkal, Rao Muhammad Anwer, Michael Felsberg, Jorma Laaksonen, Thamar Solorio, Monojit Choudhury, Ivan Laptev, Mubarak Shah, Salman Khan, Fahad Khan
2024	J	`jnl`	Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL. CoRR Ghada Sokar, Johan S. Obando-Ceron, Aaron C. Courville, Hugo Larochelle, Pablo Samuel Castro
2024	J	`jnl`	In deep reinforcement learning, a pruned network is a good network. CoRR Johan S. Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro
2024	A*	`conf`	In value-based deep reinforcement learning, a pruned network is a good network. ICML Johan S. Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro
2024	J	`jnl`	Mixture of Experts in a Mixture of RL settings. RLJ Timon Willi, Johan S. Obando-Ceron, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Pablo Samuel Castro
2024	J	`jnl`	Mixture of Experts in a Mixture of RL settings. CoRR Timon Willi, Johan S. Obando-Ceron, Jakob N. Foerster, Karolina Dziugaite, Pablo Samuel Castro
2024	A*	`conf`	Mixtures of Experts Unlock Parameter Scaling for Deep RL. ICML Johan S. Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro
2024	J	`jnl`	Mixtures of Experts Unlock Parameter Scaling for Deep RL. CoRR Johan S. Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob N. Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro
2024	J	`jnl`	Neuroplastic Expansion in Deep Reinforcement Learning. CoRR Jiashun Liu, Johan S. Obando-Ceron, Aaron C. Courville, Ling Pan
2024	J	`jnl`	On the consistency of hyper-parameter selection in value-based deep reinforcement learning. RLJ Johan S. Obando-Ceron, João Guilherme Madeira Araújo, Aaron C. Courville, Pablo Samuel Castro
2024	J	`jnl`	On the consistency of hyper-parameter selection in value-based deep reinforcement learning. CoRR Johan S. Obando-Ceron, João G. M. Araújo, Aaron C. Courville, Pablo Samuel Castro
2023	A*	`conf`	Bigger, Better, Faster: Human-level Atari with human-level efficiency. ICML Max Schwarzer, Johan S. Obando-Ceron, Aaron C. Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro
2023	J	`jnl`	Bigger, Better, Faster: Human-level Atari with human-level efficiency. CoRR Max Schwarzer, Johan S. Obando-Ceron, Aaron C. Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro
2023	J	`jnl`	JaxPruner: A concise library for sparsity research. CoRR 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
2023	J	`jnl`	Probabilistic Multimodal Depth Estimation Based on Camera-LiDAR Sensor Fusion. CoRR Johan S. Obando-Ceron, Victor Romero-Cano, Sildomar Monteiro
2023	A*	`conf`	Small batch deep reinforcement learning. NeurIPS Johan S. Obando-Ceron, Marc G. Bellemare, Pablo Samuel Castro
2023	J	`jnl`	Small batch deep reinforcement learning. CoRR Johan S. Obando-Ceron, Marc G. Bellemare, Pablo Samuel Castro
2023	—	`conf`	The Small Batch Size Anomaly in Multistep Deep Reinforcement Learning. Tiny Papers @ ICLR Johan S. Obando-Ceron, Marc G. Bellemare, Pablo Samuel Castro
2021	A*	`conf`	Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research. ICML Johan S. Obando-Ceron, Pablo Samuel Castro
2020	J	`jnl`	Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research. CoRR Johan S. Obando-Ceron, Pablo Samuel Castro
2019	J	`jnl`	Divide and Conquer: an Accurate Machine Learning Algorithm to Process Split Videos on a Parallel Processing Infrastructure. CoRR Walter M. Mayor Toro, Juan Carlos Perafan Villota, Oscar H. Mondragon, Johan S. Obando-Ceron
2019	J	`jnl`	Exploiting the potential of deep reinforcement learning for classification tasks in high-dimensional and unstructured data. CoRR Johan S. Obando-Ceron, Victor Romero-Cano, Walter Mayor Toro