Jason Yosinski
Jason Yosinski
Windscape AI; ML Collective
Verified email at - Homepage
Cited by
Cited by
How transferable are features in deep neural networks?
J Yosinski, J Clune, Y Bengio, H Lipson
Advances in neural information processing systems 27, 2014
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
Understanding neural networks through deep visualization
J Yosinski, J Clune, A Nguyen, T Fuchs, H Lipson
ICML Deep Learning Workshop, 2015
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
Hamiltonian neural networks
S Greydanus, M Dzamba, J Yosinski
Advances in neural information processing systems 32, 2019
An intriguing failing of convolutional neural networks and the coordconv solution
R Liu, J Lehman, P Molino, F Petroski Such, E Frank, A Sergeev, ...
Advances in neural information processing systems 31, 2018
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
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
arXiv preprint arXiv:2206.04615, 2022
Synthesizing the preferred inputs for neurons in neural networks via deep generator networks
A Nguyen, A Dosovitskiy, J Yosinski, T Brox, J Clune
Advances in neural information processing systems 29, 2016
Svcca: Singular vector canonical correlation analysis for deep learning dynamics and interpretability
M Raghu, J Gilmer, J Yosinski, J Sohl-Dickstein
Advances in neural information processing systems 30, 2017
Deep generative stochastic networks trainable by backprop
Y Bengio, E Thibodeau-Laufer, G Alain, J Yosinski
arXiv preprint arXiv:1306.1091, 2013
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
Deconstructing lottery tickets: Zeros, signs, and the supermask
H Zhou, J Lan, R Liu, J Yosinski
Advances in neural information processing systems 32, 2019
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
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
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
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
Measuring the intrinsic dimension of objective landscapes
C Li, H Farkhoor, R Liu, J Yosinski
arXiv preprint arXiv:1804.08838, 2018
Supermasks in superposition
M Wortsman, V Ramanujan, R Liu, A Kembhavi, M Rastegari, J Yosinski, ...
Advances in Neural Information Processing Systems 33, 15173-15184, 2020
Faster neural networks straight from jpeg
L Gueguen, A Sergeev, B Kadlec, R Liu, J Yosinski
Advances in Neural Information Processing Systems 31, 2018
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