Jason Yosinski
Jason Yosinski
ML Collective; Recursion Pharmaceuticals
Verified email at uber.com - Homepage
Title
Cited by
Cited by
Year
How transferable are features in deep neural networks?
J Yosinski, J Clune, Y Bengio, H Lipson
arXiv preprint arXiv:1411.1792, 2014
57182014
Deep neural networks are easily fooled: High confidence predictions for unrecognizable images
A Nguyen, J Yosinski, J Clune
Proceedings of the IEEE conference on computer vision and pattern …, 2015
22372015
Understanding neural networks through deep visualization
J Yosinski, J Clune, A Nguyen, T Fuchs, H Lipson
ICML Deep Learning Workshop, 2015
14712015
Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space
A Nguyen, J Clune, Y Bengio, A Dosovitskiy, J Yosinski
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
4912016
Synthesizing the preferred inputs for neurons in neural networks via deep generator networks
A Nguyen, A Dosovitskiy, J Yosinski, T Brox, J Clune
arXiv preprint arXiv:1605.09304, 2016
4302016
Deep generative stochastic networks trainable by backprop
Y Bengio, E Thibodeau-Laufer, G Alain, J Yosinski
arXiv preprint arXiv:1306.1091, 2013
3702013
Advances in Neural Information Processing Systems I
L Davis, DS Touretzky
Curran Associates Inc, 379-387, 1989
317*1989
An intriguing failing of convolutional neural networks and the coordconv solution
R Liu, J Lehman, P Molino, FP Such, E Frank, A Sergeev, J Yosinski
arXiv preprint arXiv:1807.03247, 2018
3152018
Time-series extreme event forecasting with neural networks at uber
N Laptev, J Yosinski, LE Li, S Smyl
International conference on machine learning 34, 1-5, 2017
2462017
Svcca: Singular vector canonical correlation analysis for deep learning dynamics and interpretability
M Raghu, J Gilmer, J Yosinski, J Sohl-Dickstein
arXiv preprint arXiv:1706.05806, 2017
2442017
Multifaceted feature visualization: Uncovering the different types of features learned by each neuron in deep neural networks
A Nguyen, J Yosinski, J Clune
arXiv preprint arXiv:1602.03616, 2016
2102016
Convergent Learning: Do different neural networks learn the same representations?
Y Li, J Yosinski, J Clune, H Lipson, J Hopcroft
International Conference on Learning Representations (ICLR), 2016
1742016
Hamiltonian neural networks
S Greydanus, M Dzamba, J Yosinski
arXiv preprint arXiv:1906.01563, 2019
1692019
The surprising creativity of digital evolution
J Lehman, J Clune, D Misevic, C Adami, L Altenberg, J Beaulieu, ...
Artificial Life Conference Proceedings, 55-56, 2018
136*2018
Automated identification of northern leaf blight-infected maize plants from field imagery using deep learning
C DeChant, T Wiesner-Hanks, S Chen, EL Stewart, J Yosinski, MA Gore, ...
Phytopathology 107 (11), 1426-1432, 2017
1202017
Measuring the intrinsic dimension of objective landscapes
C Li, H Farkhoor, R Liu, J Yosinski
arXiv preprint arXiv:1804.08838, 2018
1102018
Plug and play language models: A simple approach to controlled text generation
S Dathathri, A Madotto, J Lan, J Hung, E Frank, P Molino, J Yosinski, ...
arXiv preprint arXiv:1912.02164, 2019
1082019
Deconstructing lottery tickets: Zeros, signs, and the supermask
H Zhou, J Lan, R Liu, J Yosinski
arXiv preprint arXiv:1905.01067, 2019
1032019
Recombinator networks: Learning coarse-to-fine feature aggregation
S Honari, J Yosinski, P Vincent, C Pal
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
992016
Evolving robot gaits in hardware: the HyperNEAT generative encoding vs. parameter optimization.
J Yosinski, J Clune, D Hidalgo, S Nguyen, JC Zagal, H Lipson
ECAL, 890-897, 2011
842011
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