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Ilya Sutskever
Ilya Sutskever
Co-Founder and Chief Scientist of OpenAI
openai.com üzerinde doğrulanmış e-posta adresine sahip - Ana Sayfa
Başlık
Alıntı yapanlar
Alıntı yapanlar
Yıl
Imagenet classification with deep convolutional neural networks
A Krizhevsky, I Sutskever, GE Hinton
Advances in neural information processing systems 25, 2012
167141*2012
Tensorflow: Large-scale machine learning on heterogeneous distributed systems
M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ...
arXiv preprint arXiv:1603.04467, 2016
57451*2016
Dropout: a simple way to prevent neural networks from overfitting
N Srivastava, G Hinton, A Krizhevsky, I Sutskever, R Salakhutdinov
The journal of machine learning research 15 (1), 1929-1958, 2014
539092014
Distributed representations of words and phrases and their compositionality
T Mikolov, I Sutskever, K Chen, GS Corrado, J Dean
Advances in neural information processing systems 26, 2013
457452013
Language models are few-shot learners
TB Brown
arXiv preprint arXiv:2005.14165, 2020
357562020
Sequence to Sequence Learning with Neural Networks
I Sutskever
arXiv preprint arXiv:1409.3215, 2014
281232014
Learning transferable visual models from natural language supervision
A Radford, JW Kim, C Hallacy, A Ramesh, G Goh, S Agarwal, G Sastry, ...
International conference on machine learning, 8748-8763, 2021
248212021
Mastering the game of Go with deep neural networks and tree search
D Silver, A Huang, CJ Maddison, A Guez, L Sifre, G Van Den Driessche, ...
nature 529 (7587), 484-489, 2016
205392016
Intriguing properties of neural networks
C Szegedy
arXiv preprint arXiv:1312.6199, 2013
181212013
Language models are unsupervised multitask learners
A Radford, J Wu, R Child, D Luan, D Amodei, I Sutskever
OpenAI blog 1 (8), 9, 2019
145832019
Improving neural networks by preventing co-adaptation of feature detectors
GE Hinton
arXiv preprint arXiv:1207.0580, 2012
117482012
Improving language understanding by generative pre-training
A Radford
116892018
Infogan: Interpretable representation learning by information maximizing generative adversarial nets
X Chen, Y Duan, R Houthooft, J Schulman, I Sutskever, P Abbeel
Advances in neural information processing systems 29, 2016
6828*2016
On the importance of initialization and momentum in deep learning
I Sutskever, J Martens, G Dahl, G Hinton
International conference on machine learning, 1139-1147, 2013
65632013
Gpt-4 technical report
J Achiam, S Adler, S Agarwal, L Ahmad, I Akkaya, FL Aleman, D Almeida, ...
arXiv preprint arXiv:2303.08774, 2023
57272023
Zero-shot text-to-image generation
A Ramesh, M Pavlov, G Goh, S Gray, C Voss, A Radford, M Chen, ...
International conference on machine learning, 8821-8831, 2021
50012021
Recurrent neural network regularization
W Zaremba
arXiv preprint arXiv:1409.2329, 2014
38502014
Evaluating large language models trained on code
M Chen, J Tworek, H Jun, Q Yuan, HPDO Pinto, J Kaplan, H Edwards, ...
arXiv preprint arXiv:2107.03374, 2021
33102021
Robust speech recognition via large-scale weak supervision
A Radford, JW Kim, T Xu, G Brockman, C McLeavey, I Sutskever
International conference on machine learning, 28492-28518, 2023
32262023
Glide: Towards photorealistic image generation and editing with text-guided diffusion models
A Nichol, P Dhariwal, A Ramesh, P Shyam, P Mishkin, B McGrew, ...
arXiv preprint arXiv:2112.10741, 2021
31052021
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