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ORCIDJohan S. Obando-Ceron
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Conference and Workshop Papers
- 2024
[c6]Johan Samir Obando-Ceron, Aaron C. Courville, Pablo Samuel Castro:
In value-based deep reinforcement learning, a pruned network is a good network. ICML 2024- [c5]Johan Samir 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 - 2023
- [c4]Johan Samir 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 Samir 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 - 2021
- [c1]Johan Samir Obando-Ceron, Pablo Samuel Castro:
Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research. ICML 2021: 1373-1383
Informal and Other Publications
- 2024
- [i11]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) - [i10]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) - [i9]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) - [i8]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) - 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 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) - 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) - 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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