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← Authors

Junhyuk Oh

20 papers · 2015–2025 · 5 conferences · across top CS/AI conferences

Achievements

Jump to papers ↓
+11 more ↓ 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (5) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🏃 Academic Marathon (10)
🌈 Renaissance Researcher (5) 🐝 Cross-Pollinator (13) 🌍 Conference Polyglot (5) 🌟 Keyword Trendsetter Combo (3) 🧬 Topic Evolution 🏆 Grand Slam 💎 Century Club (20) 🔥 Unstoppable (9) 📈 Trend Setter 🗃️ Keyword Collector (76) ❓ The Questioner

Conferences

NIPS (10) ICLR (4) ICML (4) AAAI (1) CVPR (1)

Top co-authors

Honglak Lee (8) Satinder Singh (8) Zhongwen Xu (7) David Silver (6) Matteo Hessel (6) Hado P van Hasselt (5) Satinder P. Singh (4) Vivek Veeriah (3) Tom Zahavy (3) Hado van Hasselt (2)

Research topics

Reinforcement Learning (1)

Keywords

policy gradient (3) deep reinforcement learning (3) reinforcement learning (3) neural network (2) hierarchical reinforcement learning (2) auxiliary task (2) intrinsic reward (2) model-based reinforcement learning (1) value function (1) transfer learning (1) active perception (1) exploration exploitation (1) online learning (1) weakly-supervised learning (1) off-policy learning (1) policy learning (1) temporal-difference learning (1) partial observability (1) reward design (1) reward function (1)

Papers

Learning from negative feedback, or positive feedback or both ICLR 2025 In-context Reinforcement Learning with Algorithm Distillation ICLR 2023 Deep Reinforcement Learning with Plasticity Injection NIPS 2023 Introducing Symmetries to Black Box Meta Reinforcement Learning AAAI 2022 Balancing Constraints and Rewards with Meta-Gradient D4PG ICLR 2021 Discovery of Options via Meta-Learned Subgoals NIPS 2021 What Can Learned Intrinsic Rewards Capture? ICML 2020 Discovering Reinforcement Learning Algorithms NIPS 2020 Meta-Gradient Reinforcement Learning with an Objective Discovered Online NIPS 2020 A Self-Tuning Actor-Critic Algorithm NIPS 2020 Discovery of Useful Questions as Auxiliary Tasks NIPS 2019 Contingency-Aware Exploration in Reinforcement Learning ICLR 2019 Self-Imitation Learning ICML 2018 On Learning Intrinsic Rewards for Policy Gradient Methods NIPS 2018 Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies NIPS 2018 Value Prediction Network NIPS 2017 Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning ICML 2017 Learning Transferrable Knowledge for Semantic Segmentation With Deep Convolutional Neural Network CVPR 2016 Control of Memory, Active Perception, and Action in Minecraft ICML 2016 Action-Conditional Video Prediction using Deep Networks in Atari Games NIPS 2015