Philip Bachman
Philip Bachman
Microsoft Research
Verified email at microsoft.com
Title
Cited by
Cited by
Year
Deep reinforcement learning that matters
P Henderson, R Islam, P Bachman, J Pineau, D Precup, D Meger
arXiv preprint arXiv:1709.06560, 2017
6522017
Learning deep representations by mutual information estimation and maximization
RD Hjelm, A Fedorov, S Lavoie-Marchildon, K Grewal, P Bachman, ...
arXiv preprint arXiv:1808.06670, 2018
3602018
Newsqa: A machine comprehension dataset
A Trischler, T Wang, X Yuan, J Harris, A Sordoni, P Bachman, K Suleman
arXiv preprint arXiv:1611.09830, 2016
3082016
Augmented cyclegan: Learning many-to-many mappings from unpaired data
A Almahairi, S Rajeswar, A Sordoni, P Bachman, A Courville
arXiv preprint arXiv:1802.10151, 2018
1752018
Learning representations by maximizing mutual information across views
P Bachman, RD Hjelm, W Buchwalter
Advances in Neural Information Processing Systems, 15535-15545, 2019
1432019
Learning with pseudo-ensembles
P Bachman, O Alsharif, D Precup
Advances in neural information processing systems, 3365-3373, 2014
1412014
Iterative alternating neural attention for machine reading
A Sordoni, P Bachman, A Trischler, Y Bengio
arXiv preprint arXiv:1606.02245, 2016
1002016
Machine comprehension by text-to-text neural question generation
X Yuan, T Wang, C Gulcehre, A Sordoni, P Bachman, S Subramanian, ...
arXiv preprint arXiv:1705.02012, 2017
902017
Learning algorithms for active learning
P Bachman, A Sordoni, A Trischler
arXiv preprint arXiv:1708.00088, 2017
812017
Natural language comprehension with the epireader
A Trischler, Z Ye, X Yuan, K Suleman
arXiv preprint arXiv:1606.02270, 2016
802016
Calibrating energy-based generative adversarial networks
Z Dai, A Almahairi, P Bachman, E Hovy, A Courville
arXiv preprint arXiv:1702.01691, 2017
702017
An architecture for deep, hierarchical generative models
P Bachman
Advances in Neural Information Processing Systems, 4826-4834, 2016
432016
Data generation as sequential decision making
P Bachman, D Precup
Advances in Neural Information Processing Systems, 3249-3257, 2015
412015
Natural language generation in dialogue using lexicalized and delexicalized data
S Sharma, J He, K Suleman, H Schulz, P Bachman
arXiv preprint arXiv:1606.03632, 2016
202016
Structure discovery in PPI networks using pattern-based network decomposition
P Bachman, Y Liu
Bioinformatics 25 (14), 1814-1821, 2009
122009
Variational Generative Stochastic Networks with Collaborative Shaping.
P Bachman, D Precup
ICML, 1964-1972, 2015
112015
Training deep generative models: Variations on a theme
P Bachman, D Precup
NIPS Approximate Inference Workshop, 2015
102015
Towards information-seeking agents
P Bachman, A Sordoni, A Trischler
arXiv preprint arXiv:1612.02605, 2016
72016
Vfunc: a deep generative model for functions
P Bachman, R Islam, A Sordoni, Z Ahmed
arXiv preprint arXiv:1807.04106, 2018
62018
Improved estimation in time varying models
D Precup, P Bachman
arXiv preprint arXiv:1206.6385, 2012
5*2012
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