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Active Reinforcement Learning: Observing Rewards at a Cost

Nov 24, 2020
David Krueger, Jan Leike, Owain Evans, John Salvatier

* Originally appeared at the NeurIPS 2016 "Future of Interactive Learning Machines (FILM)" workshop 

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Hidden Incentives for Auto-Induced Distributional Shift

Sep 19, 2020
David Krueger, Tegan Maharaj, Jan Leike


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AI Research Considerations for Human Existential Safety (ARCHES)

May 30, 2020
Andrew Critch, David Krueger


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Out-of-Distribution Generalization via Risk Extrapolation (REx)

Mar 13, 2020
David Krueger, Ethan Caballero, Joern-Henrik Jacobsen, Amy Zhang, Jonathan Binas, Remi Le Priol, Aaron Courville


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Scalable agent alignment via reward modeling: a research direction

Nov 19, 2018
Jan Leike, David Krueger, Tom Everitt, Miljan Martic, Vishal Maini, Shane Legg


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Uncertainty in Multitask Transfer Learning

Jul 06, 2018
Alexandre Lacoste, Boris Oreshkin, Wonchang Chung, Thomas Boquet, Negar Rostamzadeh, David Krueger


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Bayesian Hypernetworks

Apr 24, 2018
David Krueger, Chin-Wei Huang, Riashat Islam, Ryan Turner, Alexandre Lacoste, Aaron Courville

* David Krueger and Chin-Wei Huang contributed equally 

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Neural Autoregressive Flows

Apr 03, 2018
Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron Courville

* 16 pages, 10 figures, 3 tables 

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Nested LSTMs

Jan 31, 2018
Joel Ruben Antony Moniz, David Krueger

* Proceedings of the Ninth Asian Conference on Machine Learning, PMLR 77:530-544, 2017 
* Accepted at ACML 2017 

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Deep Prior

Dec 16, 2017
Alexandre Lacoste, Thomas Boquet, Negar Rostamzadeh, Boris Oreshkin, Wonchang Chung, David Krueger

* Workshop paper, Accepted at Bayesian Deep Learning workshop, NIPS 2017 

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Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations

Sep 22, 2017
David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Aaron Courville, Chris Pal

* David Krueger and Tegan Maharaj contributed equally to this work 

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A Closer Look at Memorization in Deep Networks

Jul 01, 2017
Devansh Arpit, Stanisław Jastrzębski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron Courville, Yoshua Bengio, Simon Lacoste-Julien

* Appears in Proceedings of the 34th International Conference on Machine Learning (ICML 2017), Devansh Arpit, Stanis{\l}aw Jastrz\k{e}bski, Nicolas Ballas, and David Krueger contributed equally to this work 

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Regularizing RNNs by Stabilizing Activations

Apr 26, 2016
David Krueger, Roland Memisevic


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Testing Visual Attention in Dynamic Environments

Oct 30, 2015
Philip Bachman, David Krueger, Doina Precup


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NICE: Non-linear Independent Components Estimation

Apr 10, 2015
Laurent Dinh, David Krueger, Yoshua Bengio

* 11 pages and 2 pages Appendix, workshop paper at ICLR 2015 

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Zero-bias autoencoders and the benefits of co-adapting features

Apr 08, 2015
Kishore Konda, Roland Memisevic, David Krueger


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