John D. Schulman

John D. Schulman's AcademicInfluence.com Rankings

John D. Schulman

Computer Science

#8566

World Rank

#9004

Historical Rank

Machine Learning

#3542

World Rank

#3586

Historical Rank

Artificial Intelligence

#3851

World Rank

#3907

Historical Rank

Database

#5565

World Rank

#5774

Historical Rank

computer-science Degrees

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Computer Science

John D. Schulman's Degrees

PhD Computer Science University of California, Berkeley
Bachelors Computer Science Stanford University

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John D. Schulman's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Proximal Policy Optimization Algorithms (2017) (8568)
Trust Region Policy Optimization (2015) (4825)
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets (2016) (3593)
OpenAI Gym (2016) (3297)
Theano: A Python framework for fast computation of mathematical expressions (2016) (2219)
High-Dimensional Continuous Control Using Generalized Advantage Estimation (2015) (2133)
Concrete Problems in AI Safety (2016) (1511)
Benchmarking Deep Reinforcement Learning for Continuous Control (2016) (1421)
On First-Order Meta-Learning Algorithms (2018) (1409)
Training language models to follow instructions with human feedback (2022) (797)
RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning (2016) (761)
Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations (2017) (684)
VIME: Variational Information Maximizing Exploration (2016) (619)
Spike sorting for large, dense electrode arrays (2015) (576)
Variational Lossy Autoencoder (2016) (576)
Motion planning with sequential convex optimization and convex collision checking (2014) (566)
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning (2016) (562)
Reptile: a Scalable Metalearning Algorithm (2018) (457)
Quantifying Generalization in Reinforcement Learning (2018) (448)
Finding Locally Optimal, Collision-Free Trajectories with Sequential Convex Optimization (2013) (428)
Gradient Estimation Using Stochastic Computation Graphs (2015) (336)
Leveraging Procedural Generation to Benchmark Reinforcement Learning (2019) (314)
Meta Learning Shared Hierarchies (2017) (282)
Equivalence Between Policy Gradients and Soft Q-Learning (2017) (263)
Teacher–Student Curriculum Learning (2017) (257)
Training Verifiers to Solve Math Word Problems (2021) (222)
Model-Based Reinforcement Learning via Meta-Policy Optimization (2018) (165)
WebGPT: Browser-assisted question-answering with human feedback (2021) (161)
Tracking deformable objects with point clouds (2013) (158)
Scaling Laws for Autoregressive Generative Modeling (2020) (146)
DEFENSIVE QUANTIZATION: WHEN EFFICIENCY MEETS ROBUSTNESS (2018) (145)
Gotta Learn Fast: A New Benchmark for Generalization in RL (2018) (142)
Learning from Demonstrations Through the Use of Non-rigid Registration (2013) (134)
Unsolved Problems in ML Safety (2021) (91)
UCB EXPLORATION VIA Q-ENSEMBLES (2018) (87)
Scaling up Gaussian Belief Space Planning Through Covariance-Free Trajectory Optimization and Automatic Differentiation (2014) (86)
A case study of trajectory transfer through non-rigid registration for a simplified suturing scenario (2013) (83)
Amplitude compression and profound hearing loss. (1988) (78)
Phasic Policy Gradient (2020) (75)
Curiosity-driven Exploration in Deep Reinforcement Learning via Bayesian Neural Networks (2016) (66)
Variational Information Maximizing Exploration (2016) (46)
Distribution Augmentation for Generative Modeling (2020) (41)
Sigma hulls for Gaussian belief space planning for imprecise articulated robots amid obstacles (2013) (39)
Optimizing Expectations: From Deep Reinforcement Learning to Stochastic Computation Graphs (2016) (36)
Gaussian belief space planning with discontinuities in sensing domains (2014) (30)
Policy Gradient Search: Online Planning and Expert Iteration without Search Trees (2019) (28)
Efficient Training of Language Models to Fill in the Middle (2022) (25)
Generalization in Robotic Manipulation Through The Use of Non-Rigid Registration (2013) (21)
Grasping and Fixturing as Submodular Coverage Problems (2011) (21)
Semi-Supervised Learning by Label Gradient Alignment (2019) (19)
Planning locally optimal, curvature-constrained trajectories in 3D using sequential convex optimization (2014) (17)
Scaling Laws for Reward Model Overoptimization (2022) (14)
Reinforced Variational Inference (2015) (13)
Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark (2021) (10)
UCB and InfoGain Exploration via $\boldsymbol{Q}$-Ensembles (2017) (4)
Batch size-invariance for policy optimization (2021) (4)
Gaussian Belief Space Planning for Imprecise Articulated Robots (2013) (3)
Scaling laws for single-agent reinforcement learning (2023) (3)
PixelEDL: Unsupervised Skill Discovery and Learning from Pixels (2021) (1)
Kahler-Einstein and Kahler scalar flat supermanifolds (2016) (1)
Energetics and Error Rates of Self-Correcting Quantum Memories (2008) (0)
Under review as a conference paper at ICLR 2017 # Exploration : A Study of Count-Based Exploration for Deep Reinforcement Learning (2017) (0)
Learning 2 D Linear Dynamics in Image Space Using Neural Networks (2014) (0)
4 Variational Inference as Reinforcement Learning (2015) (0)
Understanding hippocampal phase precession and phase relationships using phase response curves (2008) (0)
Conditional Augmentation for Generative Modeling (2020) (0)
Task Pipeline Specification and Scheduling (2014) (0)
Static charging: old and new mysteries (2010) (0)

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John D. Schulman's Academic­Influence.com Rankings

John D. Schulman's Degrees

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Why Is John D. Schulman Influential?

John D. Schulman's Published Works

Published Works

John D. Schulman's AcademicInfluence.com Rankings