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Soumith Chintala
Soumith Chintala
Meta AI
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Cited by
Cited by
Year
Pytorch: An imperative style, high-performance deep learning library
A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ...
Advances in Neural Information Processing Systems, 8024--8035, 2019
400452019
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
A Radford, L Metz, S Chintala
International Conference on Learning Representations, 2015
170692015
Wasserstein generative adversarial networks
M Arjovsky, S Chintala, L Bottou
International conference on machine learning, 214-223, 2017
154912017
Automatic differentiation in pytorch
A Paszke, S Gross, S Chintala, G Chanan, E Yang, Z DeVito, Z Lin, ...
Neural Information Processing Systems Autodiff Workshop, 2017
136592017
Deep generative image models using a laplacian pyramid of adversarial networks
E Denton, S Chintala, A Szlam, R Fergus
Advances in Neural Information Processing Systems, 2015
29202015
Pedestrian detection with unsupervised multi-stage feature learning
P Sermanet, K Kavukcuoglu, S Chintala, Y LeCun
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013
10892013
Semantic segmentation using adversarial networks
P Luc, C Couprie, S Chintala, J Verbeek
Neural Information Processing Systems Workshop on Adversarial Training, 2016
9502016
Convolutional neural networks applied to house numbers digit classification
P Sermanet, S Chintala, Y LeCun
International Conference on Pattern Recognition, 3288-3291, 2012
7282012
Applied machine learning at facebook: A datacenter infrastructure perspective
K Hazelwood, S Bird, D Brooks, S Chintala, U Diril, D Dzhulgakov, ...
2018 IEEE International Symposium on High Performance Computer Architecture …, 2018
6832018
Pytorch: An imperative style, high-performance deep learning library
B Steiner, Z DeVito, S Chintala, S Gross, A Paske, F Massa, A Lerer, ...
6622019
Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv 2015
A Radford, L Metz, S Chintala
arXiv preprint arXiv:1511.06434, 2015
5442015
Wasserstein gan. arXiv 2017
M Arjovsky, S Chintala, L Bottou
arXiv preprint arXiv:1701.07875 30, 2017
4742017
Pytorch distributed: Experiences on accelerating data parallel training
S Li, Y Zhao, R Varma, O Salpekar, P Noordhuis, T Li, A Paszke, J Smith, ...
Proceedings of the VLDB Endowment, 2020
4272020
Fast convolutional nets with fbfft: A GPU performance evaluation
N Vasilache, J Johnson, M Mathieu, S Chintala, S Piantino, Y LeCun
International Conference on Learning Representations, 2015
3972015
Pytorch: Tensors and dynamic neural networks in python with strong gpu acceleration
A Paszke, S Gross, S Chintala, G Chanan
PyTorch: Tensors and dynamic neural networks in Python with strong GPU …, 2017
3432017
A multipath network for object detection
S Zagoruyko, A Lerer, TY Lin, PO Pinheiro, S Gross, S Chintala, P Dollįr
British Machine Vision Conference 2016, 2016
2852016
Discovering causal signals in images
D Lopez-Paz, R Nishihara, S Chintala, B Scholkopf, L Bottou
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
2412017
Pytorch: An imperative style, high-performance deep learning library. arXiv 2019
A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ...
arXiv preprint arXiv:1912.01703, 1912
1731912
Episodic exploration for deep deterministic policies: An application to starcraft micromanagement tasks
N Usunier, G Synnaeve, Z Lin, S Chintala
arXiv preprint arXiv:1609.02993, 2016
1682016
Generalized inner loop meta-learning
E Grefenstette, B Amos, D Yarats, PM Htut, A Molchanov, F Meier, D Kiela, ...
arXiv preprint arXiv:1910.01727, 2019
1542019
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