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
5022014
A closer look at memorization in deep networks
D Krueger, N Ballas, S Jastrzebski, D Arpit, MS Kanwal, T Maharaj, ...
International Conference on Machine Learning (ICML), 2017
357*2017
A closer look at memorization in deep networks
D Arpit, S Jastrzębski, N Ballas, D Krueger, E Bengio, MS Kanwal, ...
arXiv preprint arXiv:1706.05394, 2017
3342017
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
2032016
Neural autoregressive flows
CW Huang, D Krueger, A Lacoste, A Courville
arXiv preprint arXiv:1804.00779, 2018
1202018
Zero-bias autoencoders and the benefits of co-adapting features
K Konda, R Memisevic, D Krueger
arXiv preprint arXiv:1402.3337, 2014
75*2014
Bayesian hypernetworks
D Krueger, CW Huang, R Islam, R Turner, A Lacoste, A Courville
arXiv preprint arXiv:1710.04759, 2017
612017
Regularizing rnns by stabilizing activations
D Krueger, R Memisevic
arXiv preprint arXiv:1511.08400, 2015
612015
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
332018
Nested lstms
JRA Moniz, D Krueger
Asian Conference on Machine Learning, 530-544, 2017
292017
Deep prior
A Lacoste, T Boquet, N Rostamzadeh, B Oreshkin, W Chung, D Krueger
arXiv preprint arXiv:1712.05016, 2017
20*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
102016
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
62020
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
62020
Misleading metaobjectives and hidden incentives for distributional shift
D Krueger, T Maharaj, S Legg, J Leike
Safe Machine Learning workshop at ICLR, 2019
12019
Testing visual attention in dynamic environments
P Bachman, D Krueger, D Precup
arXiv preprint arXiv:1510.08949, 2015
12015
AI Research Considerations for Human Existential Safety (ARCHES)
A Critch, D Krueger
arXiv preprint arXiv:2006.04948, 2020
2020
Hidden incentives for self-induced distributional shift
DS Krueger, T Maharaj, S Legg, J Leike
2019
Reserve Output Units for Deep Open-Set Learning
T Maharaj, D Krueger
2018
Designing Regularizers and Architectures for Recurrent Neural Networks
D Krueger
2016
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Articles 1–20