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Johan Obando-Ceron — most-cited papers & profile · Reinforcement Learning
← authors
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overview
Johan Obando-Ceron
17
papers ·
30
citations ·
5
h-index
Google Scholar ↗
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Most-cited papers
Revisiting Rainbow: Promoting more Insightful and Inclusive Deep Reinforcement Learning Research
2020 · 18 citations
Bigger, Better, Faster: Human-level Atari with human-level efficiency
2023 · 5 citations
Small batch deep reinforcement learning
2023 · 3 citations
Mixtures of Experts Unlock Parameter Scaling for Deep RL
2024 · 3 citations
Mixture of Experts in a Mixture of RL settings
2024 · 1 citations
Stable Deep Reinforcement Learning via Isotropic Gaussian Representations
2026
Asymmetric Proximal Policy Optimization: mini-critics boost LLM reasoning
2025
Simplicial Embeddings Improve Sample Efficiency in Actor-Critic Agents
2025
The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks
2025
The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning
2025
Stable Gradients for Stable Learning at Scale in Deep Reinforcement Learning
2025
Measure gradients, not activations! Enhancing neuronal activity in deep reinforcement learning
2025
In value-based deep reinforcement learning, a pruned network is a good network
2024
On the consistency of hyper-parameter selection in value-based deep reinforcement learning
2024
Neuroplastic Expansion in Deep Reinforcement Learning
2024
Top co-authors
Pablo Samuel Castro
· 14
Aaron Courville
· 11
Jiashun Liu
· 3
Jakob Foerster
· 2
Ling Pan
· 2
Timon Willi
· 2
Walter Mayor
· 2
Ali Saheb Pasand
· 1
Bo Zheng
· 1
Clare Lyle
· 1
Doina Precup
· 1
Ghada Sokar
· 1
Topics
Value-Based
Model-Based RL
Policy Gradient
Exploration
Game AI
Meta-RL
RLHF & Alignment
Multi-Agent
Offline RL