Johan S. Obando-Ceron

According to our database, Johan S. Obando-Ceron authored at least 15 papers between 2019 and 2024.

Collaborative distances:

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

2024

Neuroplastic Expansion in Deep Reinforcement Learning.

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

CoRR, 2024

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

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

RLJ, 2024

Mixtures of Experts Unlock Parameter Scaling for Deep RL.

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

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

2023

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

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

CoRR, 2023

JaxPruner: A concise library for sparsity research.

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 Bik, Woohyun Han, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann N. Dauphin, Karolina Dziugaite, Pablo Samuel Castro, Utku Evci

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 Samir 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 Samir 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 Samir 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