Theano: A Python framework for fast computation of mathematical expressions

Arvind and David E. Culler, “Dataflow architectures,” Annual Review of Computer Science 1

1986

Earlier work this paper cites.

Barak A. Pearlmutter, “Fast exact multiplication by the Hessian,” Neural Computation 6

1994

Earlier work this paper cites.

James Bergstra, Olivier Breuleux, Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, Guillaume Desjardins, Joseph Turian, David Warde-Farley, and Yoshua Bengio, “Theano: A CPU and GPU math expression compiler,” in Proceedings of the Python for Scientific Computing Conference (SciPy) (2010)

2010

Earlier work this paper cites.

James Bergstra, Frédéric Bastien, Olivier Breuleux, Pascal Lamblin, Razvan Pascanu, Olivier Delalleau, Guillaume Desjardins, David Warde-Farley, Ian J. Goodfellow, Arnaud Bergeron, and Yoshua Bengio, “Theano: Deep learning on GPUs with Python,” in Big Learning Workshop, NIPS (2011)

2011

Earlier work this paper cites.

Ronan Collobert, Koray Kavukcuoglu, and Clément Farabet, “Torch7: A matlab-like environment for machine learning,” in Big Learning Workshop, NIPS (2011)

2011

Earlier work this paper cites.

Stefan van der Walt, S. Chris Colbert, and Gael Varoquaux, “The NumPy array: A structure for efficient numerical computation,” Computing in Science and Eng. 13

2011

Earlier work this paper cites.

Frédéric Bastien, Arnaud Bergeron, Andreas Klöckner, Pascal Vincent, and Yoshua Bengio, “A common GPU n-dimensional array for Python and C,” in Big Learning Workshop, NIPS (2011)

2011

Earlier work this paper cites.

Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, James Bergstra, Ian J. Goodfellow, Arnaud Bergeron, Nicolas Bouchard, and Yoshua Bengio, “Theano: New features and speed improvements,” Deep Learning and Unsupervised Feature Learning Workshop, NIPS (2012)

Original

2012

Earlier work this paper cites.

Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton, “ImageNet classification with deep convolutional neural networks,” in Advances in Neural Information Processing Systems (2012) pp. 1097–1105

2012

Earlier work this paper cites.

Jeffrey Dean, Greg Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Mark Mao, Marc’Aurelio Ranzato, Andrew Senior, Paul Tucker, Ke Yang, Quoc V. Le, and Andrew Y. Ng, “Large scale distributed deep networks,” in Advances in Neural Information Processing Systems (2012) pp. 1223–1231

2012

Earlier work this paper cites.

Ian J. Goodfellow, David Warde-Farley, Pascal Lamblin, Vincent Dumoulin, Mehdi Mirza, Razvan Pascanu, James Bergstra, Frédéric Bastien, and Yoshua Bengio, “Pylearn2: A machine learning research library,” arXiv e-prints abs/1308.4214

Original

2013

Earlier work this paper cites.

Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, and Yann LeCun, “OverFeat: Integrated recognition, localization and detection using convolutional networks,” arXiv e-prints abs/1312.6229

Original

2013

Cited alongside, same era.

Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, and Trevor Darrell, “Caffe: Convolutional architecture for fast feature embedding,” arXiv e-prints abs/1408.5093

Original

2014

Cited alongside, same era.

Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, and Evan Shelhamer, “cuDNN: Efficient primitives for deep learning,” arXiv e-prints abs/1410.0759

Original

2014

Cited alongside, same era.

Alex Krizhevsky, “One weird trick for parallelizing convolutional neural networks,” arXiv e-prints abs/1404.5997

Original

2014

Cited alongside, same era.

Seiya Tokui, Kenta Oono, Shohei Hido, and Justin Clayton, “Chainer: a next-generation open source framework for deep learning,” in Workshop on Machine Learning Systems (LearningSys), NIPS (2015)

2015

Later among the works it cites.

Sixin Zhang, Anna E Choromanska, and Yann LeCun, “Deep learning with elastic averaging SGD,” in Advances in Neural Information Processing Systems (2015) pp. 685–693

2015

Later among the works it cites.

Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich, “Going deeper with convolutions,” in Computer Vision and Pattern Recognition (CVPR) (2015)

Original

2015

Later among the works it cites.

Li Yao, Atousa Torabi, Kyunghyun Cho, Nicolas Ballas, Christopher Pal, Hugo Larochelle, and Aaron Courville, “Describing videos by exploiting temporal structure,” in Computer Vision (ICCV), 2015 IEEE International Conference on (IEEE, 2015)

2015

Later among the works it cites.