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Supermasks in Superposition

Jun 30, 2020
Mitchell Wortsman, Vivek Ramanujan, Rosanne Liu, Aniruddha Kembhavi, Mohammad Rastegari, Jason Yosinski, Ali Farhadi


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Estimating Q(s,s') with Deep Deterministic Dynamics Gradients

Feb 21, 2020
Ashley D. Edwards, Himanshu Sahni, Rosanne Liu, Jane Hung, Ankit Jain, Rui Wang, Adrien Ecoffet, Thomas Miconi, Charles Isbell, Jason Yosinski


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Plug and Play Language Models: A Simple Approach to Controlled Text Generation

Jan 08, 2020
Sumanth Dathathri, Andrea Madotto, Janice Lan, Jane Hung, Eric Frank, Piero Molino, Jason Yosinski, Rosanne Liu


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Plug and Play Language Models: a Simple Approach to Controlled Text Generation

Dec 04, 2019
Sumanth Dathathri, Andrea Madotto, Janice Lan, Jane Hung, Eric Frank, Piero Molino, Jason Yosinski, Rosanne Liu


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First-Order Preconditioning via Hypergradient Descent

Oct 18, 2019
Ted Moskovitz, Rui Wang, Janice Lan, Sanyam Kapoor, Thomas Miconi, Jason Yosinski, Aditya Rawal


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LCA: Loss Change Allocation for Neural Network Training

Sep 03, 2019
Janice Lan, Rosanne Liu, Hattie Zhou, Jason Yosinski

* To be presented at NeurIPS 2019 

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Hamiltonian Neural Networks

Jul 07, 2019
Sam Greydanus, Misko Dzamba, Jason Yosinski

* Main paper has 8 pages and 5 figures. Under review for NeurIPS 2019 

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Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask

May 03, 2019
Hattie Zhou, Janice Lan, Rosanne Liu, Jason Yosinski


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Understanding Neural Networks via Feature Visualization: A survey

Apr 18, 2019
Anh Nguyen, Jason Yosinski, Jeff Clune

* A book chapter in an Interpretable ML book (http://www.interpretable-ml.org/book/

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Metropolis-Hastings Generative Adversarial Networks

Nov 28, 2018
Ryan Turner, Jane Hung, Yunus Saatci, Jason Yosinski


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The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities

Aug 14, 2018
Joel Lehman, Jeff Clune, Dusan Misevic, Christoph Adami, Lee Altenberg, Julie Beaulieu, Peter J. Bentley, Samuel Bernard, Guillaume Beslon, David M. Bryson, Patryk Chrabaszcz, Nick Cheney, Antoine Cully, Stephane Doncieux, Fred C. Dyer, Kai Olav Ellefsen, Robert Feldt, Stephan Fischer, Stephanie Forrest, Antoine Frénoy, Christian Gagné, Leni Le Goff, Laura M. Grabowski, Babak Hodjat, Frank Hutter, Laurent Keller, Carole Knibbe, Peter Krcah, Richard E. Lenski, Hod Lipson, Robert MacCurdy, Carlos Maestre, Risto Miikkulainen, Sara Mitri, David E. Moriarty, Jean-Baptiste Mouret, Anh Nguyen, Charles Ofria, Marc Parizeau, David Parsons, Robert T. Pennock, William F. Punch, Thomas S. Ray, Marc Schoenauer, Eric Shulte, Karl Sims, Kenneth O. Stanley, François Taddei, Danesh Tarapore, Simon Thibault, Westley Weimer, Richard Watson, Jason Yosinski


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An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution

Jul 09, 2018
Rosanne Liu, Joel Lehman, Piero Molino, Felipe Petroski Such, Eric Frank, Alex Sergeev, Jason Yosinski


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Measuring the Intrinsic Dimension of Objective Landscapes

Apr 24, 2018
Chunyuan Li, Heerad Farkhoor, Rosanne Liu, Jason Yosinski

* Published in ICLR 2018 

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Proceedings of NIPS 2017 Symposium on Interpretable Machine Learning

Dec 12, 2017
Andrew Gordon Wilson, Jason Yosinski, Patrice Simard, Rich Caruana, William Herlands

* 25 papers 

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SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability

Nov 08, 2017
Maithra Raghu, Justin Gilmer, Jason Yosinski, Jascha Sohl-Dickstein

* Accepted to NIPS 2017, code: https://github.com/google/svcca/ , new plots on Imagenet 

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Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space

Apr 12, 2017
Anh Nguyen, Jeff Clune, Yoshua Bengio, Alexey Dosovitskiy, Jason Yosinski

* CVPR camera-ready 

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Synthesizing the preferred inputs for neurons in neural networks via deep generator networks

Nov 23, 2016
Anh Nguyen, Alexey Dosovitskiy, Jason Yosinski, Thomas Brox, Jeff Clune

* 29 pages, 35 figures, NIPS camera-ready 

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Multifaceted Feature Visualization: Uncovering the Different Types of Features Learned By Each Neuron in Deep Neural Networks

May 07, 2016
Anh Nguyen, Jason Yosinski, Jeff Clune

* 23 pages (including SI), 24 figures 

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Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation

Apr 17, 2016
Sina Honari, Jason Yosinski, Pascal Vincent, Christopher Pal

* accepted in CVPR 2016 

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Convergent Learning: Do different neural networks learn the same representations?

Feb 28, 2016
Yixuan Li, Jason Yosinski, Jeff Clune, Hod Lipson, John Hopcroft

* Published as a conference paper at ICLR 2016 

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Understanding Neural Networks Through Deep Visualization

Jun 22, 2015
Jason Yosinski, Jeff Clune, Anh Nguyen, Thomas Fuchs, Hod Lipson

* 12 pages. To appear at ICML Deep Learning Workshop 2015 

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Can deep learning help you find the perfect match?

Jun 20, 2015
Harm de Vries, Jason Yosinski


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Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images

Apr 02, 2015
Anh Nguyen, Jason Yosinski, Jeff Clune

* To appear at CVPR 2015 

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GSNs : Generative Stochastic Networks

Mar 23, 2015
Guillaume Alain, Yoshua Bengio, Li Yao, Jason Yosinski, Eric Thibodeau-Laufer, Saizheng Zhang, Pascal Vincent

* arXiv admin note: substantial text overlap with arXiv:1306.1091 

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How transferable are features in deep neural networks?

Nov 06, 2014
Jason Yosinski, Jeff Clune, Yoshua Bengio, Hod Lipson

* Advances in Neural Information Processing Systems 27, pages 3320-3328. Dec. 2014 
* To appear in Advances in Neural Information Processing Systems 27 (NIPS 2014) 

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Deep Generative Stochastic Networks Trainable by Backprop

May 24, 2014
Yoshua Bengio, Éric Thibodeau-Laufer, Guillaume Alain, Jason Yosinski

* arXiv admin note: text overlap with arXiv:1305.0445, Also published in ICML'2014 

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Hands-free Evolution of 3D-printable Objects via Eye Tracking

Apr 19, 2013
Nick Cheney, Jeff Clune, Jason Yosinski, Hod Lipson

* 6 pages, 7 figures 

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