← Authors

Junhyuk Oh

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

Achievements

πŸƒ Academic Marathon (10) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (25) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (5) 🐝 Cross-Pollinator (13) 🌍 Conference Polyglot (5) 🌟 Keyword Trendsetter Combo (3) 🧬 Topic Evolution πŸ† Grand Slam πŸ’Ž Century Club (20) πŸ”₯ Unstoppable (9) πŸ“ˆ Trend Setter πŸ—ƒοΈ 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