John Schulman

19 papers · 2013–2024 · 5 conferences · across top CS/AI conferences

Achievements

+11 more ↓

🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (5) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🏃 Academic Marathon (11)

🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (5) 🔬 Deep Specialist (10) 🧬 Topic Evolution 👥 Mega-Team (20) 🗃️ Keyword Collector (76) 📈 Trend Setter 💎 Century Club (19) 🔥 Unstoppable (10) 🚀 Conference Pioneer

Conferences

ICML (7) NIPS (7) ICLR (2) RSS (2) CORL (1)

Top co-authors

Pieter Abbeel (9) Jacob Hilton (5) Karl Cobbe (4) Xi Chen (4) Yan Duan (4) Rein Houthooft (4) Ilya Sutskever (3) Filip De Turck (2) Jan Leike (2) Sergey Levine (2)

Keywords

deep reinforcement learning (5) reinforcement learning (5) policy gradient (4) sample efficiency (3) reward model (3) data augmentation (2) reinforcement learning from human feedback (2) exploration bonus (2) intrinsic motivation (2) neural network (2) continuous control (2) instruction following (1) image generation (1) language model alignment (1) motion planning (1) variational inference (1) model alignment (1) domain generalization (1) gradient estimation (1) policy optimization (1)

Papers

Let's Verify Step by Step ICLR 2024 Rule Based Rewards for Language Model Safety NIPS 2024 Scaling Laws for Reward Model Overoptimization ICML 2023 Batch size-invariance for policy optimization NIPS 2022 Training language models to follow instructions with human feedback NIPS 2022 Phasic Policy Gradient ICML 2021 Leveraging Procedural Generation to Benchmark Reinforcement Learning ICML 2020 Distribution Augmentation for Generative Modeling ICML 2020 Quantifying Generalization in Reinforcement Learning ICML 2019 Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations RSS 2018 Model-Based Reinforcement Learning via Meta-Policy Optimization CORL 2018 META LEARNING SHARED HIERARCHIES ICLR 2018 #Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning NIPS 2017 VIME: Variational Information Maximizing Exploration NIPS 2016 Benchmarking Deep Reinforcement Learning for Continuous Control ICML 2016 InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets NIPS 2016 Gradient Estimation Using Stochastic Computation Graphs NIPS 2015 Trust Region Policy Optimization ICML 2015 Finding Locally Optimal, Collision-Free Trajectories with Sequential Convex Optimization RSS 2013