Wojciech Zaremba

Q: What Schools Are Affiliated With Wojciech Zaremba

Wojciech Zaremba is affiliated with the following schools: University of Warsaw, New York University

Wojciech Zaremba's AcademicInfluence.com Rankings

Wojciech Zaremba

Computer Science

#574

World Rank

#594

Historical Rank

Artificial Intelligence

#83

World Rank

#86

Historical Rank

Machine Learning

#125

World Rank

#126

Historical Rank

Algorithms

#257

World Rank

#260

Historical Rank

computer-science Degrees

Wojciech Zaremba

Mathematics

#3099

World Rank

#4641

Historical Rank

Measure Theory

#2755

World Rank

#3290

Historical Rank

mathematics Degrees

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Computer Science
Mathematics

Wojciech Zaremba's Degrees

PhD Computer Science New York University
Masters Mathematics University of Warsaw

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Why Is Wojciech Zaremba Influential?

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According to Wikipedia, Wojciech Zaremba is a Polish computer scientist, a founding team member of OpenAI , where he leads both the Codex research and language teams. The teams actively work on AI that writes computer code and creating successors to GPT-3 respectively. The mission of OpenAI is to build safe artificial intelligence , and ensure that its benefits are as evenly distributed as possible.

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Wojciech Zaremba'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

Intriguing properties of neural networks (2013) (10943)
Improved Techniques for Training GANs (2016) (6705)
Spectral Networks and Locally Connected Networks on Graphs (2013) (3462)
OpenAI Gym (2016) (3297)
Recurrent Neural Network Regularization (2014) (2278)
Domain randomization for transferring deep neural networks from simulation to the real world (2017) (2025)
An Empirical Exploration of Recurrent Network Architectures (2015) (1541)
Hindsight Experience Replay (2017) (1487)
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation (2014) (1448)
Sequence Level Training with Recurrent Neural Networks (2015) (1373)
Learning dexterous in-hand manipulation (2018) (1251)
Sim-to-Real Transfer of Robotic Control with Dynamics Randomization (2017) (896)
Evaluating Large Language Models Trained on Code (2021) (767)
Solving Rubik's Cube with a Robot Hand (2019) (752)
Addressing the Rare Word Problem in Neural Machine Translation (2014) (717)
Overcoming Exploration in Reinforcement Learning with Demonstrations (2017) (560)
One-Shot Imitation Learning (2017) (522)
Learning to Execute (2014) (506)
Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research (2018) (375)
Asymmetric Actor Critic for Image-Based Robot Learning (2017) (250)
Transfer from Simulation to Real World through Learning Deep Inverse Dynamics Model (2016) (204)
Reinforcement Learning Neural Turing Machines (2015) (170)
Reinforcement Learning Neural Turing Machines - Revised (2015) (155)
Domain Randomization and Generative Models for Robotic Grasping (2017) (135)
Learning Simple Algorithms from Examples (2015) (98)
Deep Neural Networks Predict Category Typicality Ratings for Images (2015) (68)
B-test: A Non-parametric, Low Variance Kernel Two-sample Test (2013) (67)
Learning to Discover Efficient Mathematical Identities (2014) (52)
Asymmetric self-play for automatic goal discovery in robotic manipulation (2021) (49)
B-tests: Low Variance Kernel Two-Sample Tests (2013) (23)
Extensions and Limitations of the Neural GPU (2016) (19)
Scale-invariant learning and convolutional networks (2015) (19)
A Generalizable Approach to Learning Optimizers (2021) (17)
Taxonomic Prediction with Tree-Structured Covariances (2013) (12)
Convolutional networks and learning invariant to homogeneous multiplicative scalings (2015) (11)
RECURRENTNEURAL NETWORK REGULARIZATION (2014) (9)
Discriminative training of CRF models with probably submodular constraints (2016) (6)
Learning from M/EEG Data with Variable Brain Activation Delays (2013) (6)
Learning Algorithms from Data (2016) (4)
Modeling the variability of EEG/MEG data through statistical machine learning (2012) (4)
Predicting Sim-to-Real Transfer with Probabilistic Dynamics Models (2020) (2)
Global-Local Graph Neural Networks for Node-Classification (2022) (0)
L IMITATIONS OF THE N EURAL GPU (2016) (0)
XTENSIONS AND L IMITATIONS OF THE N EURAL GPU (2017) (0)

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Other Resources About Wojciech Zaremba

What Schools Are Affiliated With Wojciech Zaremba?

Wojciech Zaremba is affiliated with the following schools:

Wojciech Zaremba's Academic­Influence.com Rankings

Wojciech Zaremba's Degrees

Similar Degrees You Can Earn

Why Is Wojciech Zaremba Influential?

Wojciech Zaremba's Published Works

Published Works

Other Resources About Wojciech Zaremba

What Schools Are Affiliated With Wojciech Zaremba?

Wojciech Zaremba's AcademicInfluence.com Rankings