I. Sutskever

发表

Distributed Representations of Words and Phrases and their Compositionality pdf

Jeffrey Dean, Tomas Mikolov, Gregory S. Corrado, 2013, NIPS.

Sequence to Sequence Learning with Neural Networks

Quoc V. Le, Oriol Vinyals, Ilya Sutskever, 2014, NIPS.

Language Models are Few-Shot Learners pdf

Mark Chen, Ilya Sutskever, Alec Radford, 2020, NeurIPS.

ImageNet classification with deep convolutional neural networks

Geoffrey E. Hinton, Ilya Sutskever, Alex Krizhevsky, 2012, Commun. ACM.

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems pdf

Martín Abadi, Martin Wattenberg, Michael Isard, 2016, ArXiv.

Dropout: a simple way to prevent neural networks from overfitting

Nitish Srivastava, Geoffrey E. Hinton, Ruslan Salakhutdinov, 2014, J. Mach. Learn. Res..

Jukebox: A Generative Model for Music pdf

Ilya Sutskever, Alec Radford, Heewoo Jun, 2020, ArXiv.

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

J. Schulman, P. Abbeel, Rein Houthooft, 2016, NIPS.

FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models pdf

David Duvenaud, Ilya Sutskever, Ricky T. Q. Chen, 2018, ICLR.

On the importance of initialization and momentum in deep learning

Geoffrey E. Hinton, Ilya Sutskever, George E. Dahl, 2013, ICML.

Intriguing properties of neural networks pdf

Joan Bruna, Dumitru Erhan, Wojciech Zaremba, 2013, ICLR.

Mastering the game of Go with deep neural networks and tree search

Demis Hassabis, Koray Kavukcuoglu, David Silver, 2016, Nature.

GPT-4 Technical Report

Henrique Pondé de Oliveira Pinto, Daniel P. Mossing, Vitchyr H. Pong, 2023, 2303.08774.

Learning Transferable Visual Models From Natural Language Supervision

Ilya Sutskever, Alec Radford, Gabriel Goh, 2021, ICML.

Language Models are Unsupervised Multitask Learners

Ilya Sutskever, Alec Radford, David Luan, 2019 .

Variational Lossy Autoencoder pdf

Pieter Abbeel, Xi Chen, Tim Salimans, 2016, ICLR.

GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Prafulla Dhariwal, Ilya Sutskever, Alex Nichol, 2021, ICML.

Zero-Shot Text-to-Image Generation

Alec Radford, Ilya Sutskever, Mark Chen, 2021, ICML.

Generating Long Sequences with Sparse Transformers pdf

Ilya Sutskever, Alec Radford, Scott Gray, 2019, ArXiv.

Improving neural networks by preventing co-adaptation of feature detectors

Geoffrey E. Hinton, R. Salakhutdinov, A. Krizhevsky, 2012, ArXiv.

Dota 2 with Large Scale Deep Reinforcement Learning

Jakub W. Pachocki, Henrique Pondé de Oliveira Pinto, F. Wolski, 2019, ArXiv.

Generative Language Modeling for Automated Theorem Proving pdf

Ilya Sutskever, Stanislas Polu, Ilya Sutskever, 2020, ArXiv.

Neural GPUs Learn Algorithms

Lukasz Kaiser, Ilya Sutskever, Lukasz Kaiser, 2015, ICLR.

Grammar as a Foreign Language

Geoffrey E. Hinton, Lukasz Kaiser, Oriol Vinyals, 2014, NIPS.

Learning to Execute pdf

Wojciech Zaremba, Ilya Sutskever, Ilya Sutskever, 2014, ArXiv.

On the Convergence Properties of Contrastive Divergence

Ilya Sutskever, Tijmen Tieleman, Ilya Sutskever, 2010, AISTATS.

Generative Pretraining From Pixels

Mark Chen, Ilya Sutskever, Alec Radford, 2020, ICML.

Some Considerations on Learning to Explore via Meta-Reinforcement Learning pdf

Pieter Abbeel, Xi Chen, Ilya Sutskever, 2018, ICLR 2018.

Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments

P. Abbeel, Ilya Sutskever, Igor Mordatch, 2017, ICLR.

Evaluating Large Language Models Trained on Code pdf

Wojciech Zaremba, Lukasz Kaiser, Peter Welinder, 2021, ArXiv.

Consistency Models

Prafulla Dhariwal, Ilya Sutskever, Mark Chen, 2023, ICML.

Let's Verify Step by Step

J. Schulman, Ilya Sutskever, Karl Cobbe, 2023, ICLR.

Quoc V. Le, Tomas Mikolov, Ilya Sutskever, 2013, ArXiv.

Adding Gradient Noise Improves Learning for Very Deep Networks

Quoc V. Le, Lukasz Kaiser, James Martens, 2015, ArXiv.

Generating Text with Recurrent Neural Networks

Ilya Sutskever, James Martens, Geoffrey E. Hinton, 2011, ICML.

Robust Speech Recognition via Large-Scale Weak Supervision

Jong Wook Kim, Alec Radford, Ilya Sutskever, 2022, ICML.

Evolution Strategies as a Scalable Alternative to Reinforcement Learning pdf

Xi Chen, Tim Salimans, Ilya Sutskever, 2017, ArXiv.

RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning pdf

Peter L. Bartlett, Pieter Abbeel, Xi Chen, 2016, ArXiv.

Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision

Adrien Ecoffet, Pavel Izmailov, J. Leike, 2023, ArXiv.

Deep double descent: where bigger models and more data hurt pdf

Boaz Barak, Ilya Sutskever, Gal Kaplun, 2019, ICLR.

One-Shot Imitation Learning

Marcin Andrychowicz, Wojciech Zaremba, Pieter Abbeel, 2017, NIPS.

Continuous Deep Q-Learning with Model-based Acceleration pdf

Sergey Levine, Ilya Sutskever, Shixiang Gu, 2016, ICML.

Emergent Complexity via Multi-Agent Competition pdf

Jakub W. Pachocki, Igor Mordatch, Ilya Sutskever, 2017, ICLR.

Neural Random Access Machines

Marcin Andrychowicz, Ilya Sutskever, Karol Kurach, 2015, ERCIM News.

MuProp: Unbiased Backpropagation for Stochastic Neural Networks pdf

Sergey Levine, Ilya Sutskever, Andriy Mnih, 2015, ICLR.

Extensions and Limitations of the Neural GPU pdf

Wojciech Zaremba, Ilya Sutskever, Eric Price, 2016, ArXiv.

Reinforcement Learning Neural Turing Machines

Wojciech Zaremba, I. Sutskever, 2015, ArXiv.

An Empirical Exploration of Recurrent Network Architectures

Wojciech Zaremba, Ilya Sutskever, Rafal Józefowicz, 2015, ICML.

Addressing the Rare Word Problem in Neural Machine Translation

Quoc V. Le, Wojciech Zaremba, Oriol Vinyals, 2014, ACL.

Recurrent Neural Network Regularization pdf

Wojciech Zaremba, Oriol Vinyals, Ilya Sutskever, 2014, ArXiv.

Multi-task Sequence to Sequence Learning pdf

Quoc V. Le, Lukasz Kaiser, Oriol Vinyals, 2015, ICLR.

RL: FAST REINFORCEMENT LEARNING VIA SLOW REINFORCEMENT LEARNING

J. Schulman, P. Abbeel, P. Bartlett, 2016 .

Deep, Narrow Sigmoid Belief Networks Are Universal Approximators

Geoffrey E. Hinton, Ilya Sutskever, Ilya Sutskever, 2008, Neural Computation.

Distribution Augmentation for Generative Modeling

Mark Chen, Ilya Sutskever, Alec Radford, 2020, ICML.

GPT-4 Technical Report

Henrique Pondé de Oliveira Pinto, OpenAI, Daniel P. Mossing, 2023, 2303.08774.

P ERFECT : Prompt-free and Efficient Language Model Fine-Tuning

Teven Le Scao, Patrick von Platen, Quentin de Laroussilhe, 2021 .

Move Evaluation in Go Using Deep Convolutional Neural Networks pdf

David Silver, Ilya Sutskever, Chris J. Maddison, 2014, ICLR.

Mimicking Go Experts with Convolutional Neural Networks

Vinod Nair, I. Sutskever, 2008, ICANN.

GPT-4 Technical Report

Henrique Pondé de Oliveira Pinto, Daniel P. Mossing, Vitchyr H. Pong, 2023, 2303.08774.

Unsupervised Neural Machine Translation with Generative Language Models Only pdf

Ilya Sutskever, Alec Radford, Harrison Edwards, 2021, ArXiv.

Formal Mathematics Statement Curriculum Learning

Jesse Michael Han, I. Babuschkin, Ilya Sutskever, 2022, ICLR.

Modelling Relational Data using Bayesian Clustered Tensor Factorization

Joshua B. Tenenbaum, Ruslan Salakhutdinov, Ilya Sutskever, 2009, NIPS.

Learning Factored Representations in a Deep Mixture of Experts pdf

Marc'Aurelio Ranzato, Ilya Sutskever, David Eigen, 2013, ICLR.

Language Models are Few-Shot Learners

Tom B. Brown, Daniel M. Ziegler, Jeff Wu, 2020, NeurIPS.

GeDi: Generative Discriminator Guided Decoding for Faster Controllable Sequence Generation

Teven Le Scao, Patrick von Platen, R. Socher, 2021 .

One-Step Diffusion Distillation via Deep Equilibrium Models

Siddhant M. Jayakumar, J. Z. Kolter, Raphael Lopez Kaufman, 2023, NeurIPS.

Learning to Generate Reviews and Discovering Sentiment pdf

Ilya Sutskever, Alec Radford, Rafal Józefowicz, 2017, ArXiv.

Synthesizing Robust Adversarial Examples

Anish Athalye, I. Sutskever, 2017, 1707.07397.

Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning

R. Zemel, Kevin Swersky, Daniel Tarlow, 2013, ICML.

Geoffrey E. Hinton, Ilya Sutskever, Andriy Mnih, 2007, AISTATS.

Third-Person Imitation Learning pdf

Pieter Abbeel, Ilya Sutskever, Bradly C. Stadie, 2017, ICLR.

Learning Recurrent Neural Networks with Hessian-Free Optimization

Ilya Sutskever, James Martens, Ilya Sutskever, 2011, ICML.

An online sequence-to-sequence model for noisy speech recognition pdf

Navdeep Jaitly, George Tucker, Ilya Sutskever, 2017, ArXiv.

Learning online alignments with continuous rewards policy gradient

Navdeep Jaitly, Ilya Sutskever, Chung-Cheng Chiu, 2016, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

A Neural Transducer

Quoc V. Le, Navdeep Jaitly, Ilya Sutskever, 2015, 1511.04868.

An Online Sequence-to-Sequence Model Using Partial Conditioning

Samy Bengio, Quoc V. Le, Navdeep Jaitly, 2015, NIPS.

Neural Programmer: Inducing Latent Programs with Gradient Descent pdf

Quoc V. Le, Ilya Sutskever, Arvind Neelakantan, 2015, ICLR.

Reinforcement Learning Neural Turing Machines - Revised

Wojciech Zaremba, Ilya Sutskever, Ilya Sutskever, 2015 .

Zero-shot sampling of adversarial entities in biomedical question answering

Christopher A. Choquette-Choo, Daniel M. Ziegler, Alec Radford, 2024, 2402.10527.

Night Owls and Majestic Whales: Modeling Metaphor Comprehension as a Rational Speech Act over Vector Representations of Lexical Semantics

Daniel M. Ziegler, Alec Radford, T. Henighan, 2022 .

Scaling and evaluating sparse autoencoders

Alec Radford, J. Leike, Leo Gao, 2024, ArXiv.

The Recurrent Temporal Restricted Boltzmann Machine

Geoffrey E. Hinton, Graham W. Taylor, Ilya Sutskever, 2008, NIPS.

Learning Multilevel Distributed Representations for High-Dimensional Sequences

Geoffrey E. Hinton, Ilya Sutskever, Ilya Sutskever, 2007, AISTATS.

The Importance of Sampling inMeta-Reinforcement Learning

Pieter Abbeel, Peter Chen, Ilya Sutskever, 2018, NeurIPS.

Grapes Leaf Disease Detection using Convolutional Neural Network

Tanmay Anant Wagh, R. M. Samant, Sharvil V. Gujarathi, 2019, International Journal of Computer Applications.

Towards Principled Unsupervised Learning pdf

Oriol Vinyals, Karol Gregor, Ilya Sutskever, 2015, ArXiv.

Cardinality Restricted Boltzmann Machines

Ryan P. Adams, Ruslan Salakhutdinov, Richard S. Zemel, 2012, NIPS.

Training Deep and Recurrent Networks with Hessian-Free Optimization

Ilya Sutskever, James Martens, Ilya Sutskever, 2012, Neural Networks: Tricks of the Trade.

Deep Narrow Sigmoid Belief Networks Are Universal Approximators Deep Narrow Sigmoid Belief Networks Are Universal Approximators

Geoffrey E. Hinton, I. Sutskever, 2007 .

Data Normalization in the Learning of Restricted Boltzmann Machines

Ilya Sutskever, Yichuan Tang, I. Sutskever, 2011 .