David Scott Krueger
Title
Cited by
Cited by
Year
Nice: Non-linear independent components estimation
L Dinh, D Krueger, Y Bengio
arXiv preprint arXiv:1410.8516, 2014
4302014
A closer look at memorization in deep networks
D Arpit, S Jastrzębski, N Ballas, D Krueger, E Bengio, MS Kanwal, ...
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
314*2017
Zoneout: Regularizing rnns by randomly preserving hidden activations
D Krueger, T Maharaj, J Kramár, M Pezeshki, N Ballas, NR Ke, A Goyal, ...
arXiv preprint arXiv:1606.01305, 2016
1902016
Neural autoregressive flows
CW Huang, D Krueger, A Lacoste, A Courville
arXiv preprint arXiv:1804.00779, 2018
922018
Zero-bias autoencoders and the benefits of co-adapting features
K Konda, R Memisevic, D Krueger
arXiv preprint arXiv:1402.3337, 2014
74*2014
Bayesian hypernetworks
D Krueger, CW Huang, R Islam, R Turner, A Lacoste, A Courville
arXiv preprint arXiv:1710.04759, 2017
572017
Regularizing rnns by stabilizing activations
D Krueger, R Memisevic
arXiv preprint arXiv:1511.08400, 2015
562015
Scalable agent alignment via reward modeling: a research direction
J Leike, D Krueger, T Everitt, M Martic, V Maini, S Legg
arXiv preprint arXiv:1811.07871, 2018
252018
Nested lstms
JRA Moniz, D Krueger
arXiv preprint arXiv:1801.10308, 2018
252018
Deep prior
A Lacoste, T Boquet, N Rostamzadeh, B Oreshkin, W Chung, D Krueger
arXiv preprint arXiv:1712.05016, 2017
17*2017
Active reinforcement learning: Observing rewards at a cost
D Krueger, J Leike, O Evans, J Salvatier
Future of Interactive Learning Machines, NIPS Workshop, 2016
72016
Out-of-Distribution Generalization via Risk Extrapolation (REx)
D Krueger, E Caballero, JH Jacobsen, A Zhang, J Binas, RL Priol, ...
arXiv preprint arXiv:2003.00688, 2020
12020
Testing visual attention in dynamic environments
P Bachman, D Krueger, D Precup
arXiv preprint arXiv:1510.08949, 2015
12015
MISLEADING META-OBJECTIVES AND HIDDEN INCEN-TIVES FOR DISTRIBUTIONAL SHIFT
D Krueger, T Maharaj, S Legg, J Leike
1
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims
M Brundage, S Avin, J Wang, H Belfield, G Krueger, G Hadfield, H Khlaaf, ...
arXiv preprint arXiv:2004.07213, 2020
2020
Reserve Output Units for Deep Open-Set Learning
T Maharaj, D Krueger
2018
Designing Regularizers and Architectures for Recurrent Neural Networks
D Krueger
2016
Memorization in Recurrent Neural Networks
T Maharaj, D Krueger, T Coojimans
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Articles 1–18