Johan S. Obando-Ceron

According to our database, Johan S. Obando-Ceron authored at least 26 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Stable Gradients for Stable Learning at Scale in Deep Reinforcement Learning.

Roger Creus Castanyer, Johan S. Obando-Ceron, Lu Li, Pierre-Luc Bacon, Glen Berseth, Aaron C. Courville, Pablo Samuel Castro

CoRR, June, 2025

The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning.

Jiashun Liu, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Ling Pan

CoRR, June, 2025

The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks.

Walter Mayor, Johan S. Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro

CoRR, June, 2025

Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn.

Hongyao Tang, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Glen Berseth

CoRR, June, 2025

Measure gradients, not activations! Enhancing neuronal activity in deep reinforcement learning.

Jiashun Liu, Zihao Wu, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Ling Pan

CoRR, May, 2025

Kaleidoscope: In-language Exams for Massively Multilingual Vision Evaluation.

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

CoRR, April, 2025

Adaptive Computation Pruning for the Forgetting Transformer.

Zhixuan Lin, Johan S. Obando-Ceron, Xu Owen He, Aaron C. Courville

CoRR, April, 2025

Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training.

Brian R. Bartoldson, Siddarth Venkatraman, James Diffenderfer, Moksh Jain, Tal Ben-Nun, Seanie Lee, Minsu Kim, Johan S. Obando-Ceron, Yoshua Bengio, Bhavya Kailkhura

CoRR, March, 2025

Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL.

Ghada Sokar, Johan S. Obando-Ceron, Aaron C. Courville, Hugo Larochelle, Pablo Samuel Castro

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge.

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

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Neuroplastic Expansion in Deep Reinforcement Learning.

Jiashun Liu, Johan S. Obando-Ceron, Aaron C. Courville, Ling Pan

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages.

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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages.

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

CoRR, 2024

In deep reinforcement learning, a pruned network is a good network.

Johan S. Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro

CoRR, 2024

Mixture of Experts in a Mixture of RL settings.

Timon Willi, Johan S. Obando-Ceron, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Pablo Samuel Castro

RLJ, 2024

On the consistency of hyper-parameter selection in value-based deep reinforcement learning.

Johan S. Obando-Ceron, João Guilherme Madeira Araújo, Aaron C. Courville, Pablo Samuel Castro

RLJ, 2024

Mixtures of Experts Unlock Parameter Scaling for Deep RL.

Johan S. Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro

Proceedings of the Forty-first International Conference on Machine Learning, 2024

In value-based deep reinforcement learning, a pruned network is a good network.

Johan S. Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Jaxpruner: A Concise Library for Sparsity Research.

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

Proceedings of the Conference on Parsimony and Learning, 2024

2023

Probabilistic Multimodal Depth Estimation Based on Camera-LiDAR Sensor Fusion.

Johan S. Obando-Ceron, Victor Romero-Cano, Sildomar Monteiro

CoRR, 2023

Small batch deep reinforcement learning.

Johan S. Obando-Ceron, Marc G. Bellemare, Pablo Samuel Castro

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Bigger, Better, Faster: Human-level Atari with human-level efficiency.

Max Schwarzer, Johan S. Obando-Ceron, Aaron C. Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro

Proceedings of the International Conference on Machine Learning, 2023

The Small Batch Size Anomaly in Multistep Deep Reinforcement Learning.

Johan S. Obando-Ceron, Marc G. Bellemare, Pablo Samuel Castro

Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

2021

Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research.

Johan S. Obando-Ceron, Pablo Samuel Castro

Proceedings of the 38th International Conference on Machine Learning, 2021

2019

Divide and Conquer: an Accurate Machine Learning Algorithm to Process Split Videos on a Parallel Processing Infrastructure.

Walter M. Mayor Toro, Juan Carlos Perafan Villota, Oscar H. Mondragon, Johan S. Obando-Ceron

CoRR, 2019

Exploiting the potential of deep reinforcement learning for classification tasks in high-dimensional and unstructured data.

Johan S. Obando-Ceron, Victor Romero-Cano, Walter Mayor Toro

CoRR, 2019