Vikas Verma
Vikas Verma
Aalto University
Verified email at aalto.fi
TitleCited byYear
Residual connections encourage iterative inference
S Jastrzębski, D Arpit, N Ballas, V Verma, T Che, Y Bengio
arXiv preprint arXiv:1710.04773, 2017
342017
Interpolation consistency training for semi-supervised learning
V Verma, A Lamb, J Kannala, Y Bengio, D Lopez-Paz
arXiv preprint arXiv:1903.03825, 2019
332019
Manifold mixup: Encouraging meaningful on-manifold interpolation as a regularizer
V Verma, A Lamb, C Beckham, A Courville, I Mitliagkis, Y Bengio
stat 1050, 13, 2018
262018
Manifold Mixup: Better Representations by Interpolating Hidden States
V Verma, A Lamb, C Beckham, A Najafi, I Mitliagkas, D Lopez-Paz, ...
International Conference on Machine Learning, 6438-6447, 2019
202019
Manifold mixup: Learning better representations by interpolating hidden states
V Verma, A Lamb, C Beckham, A Najafi, A Courville, I Mitliagkas, ...
102018
Selection of data storage settings for an application
MP Kumar, NH Kumar, B Padmanaabhan, V Verma
US Patent 10,262,055, 2019
92019
Deep semi-random features for nonlinear function approximation
K Kawaguchi, B Xie, V Verma, L Song
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
82018
Adversarial Mixup Resynthesizers
C Beckham, S Honari, A Lamb, V Verma, F Ghadiri, RD Hjelm, C Pal
arXiv preprint arXiv:1903.02709, 2019
52019
Generalization in machine learning via analytical learning theory
K Kawaguchi, Y Bengio, V Verma, LP Kaelbling
arXiv preprint arXiv:1802.07426, 2018
52018
Generalization in machine learning via analytical learning theory
K Kawaguchi, Y Bengio
https://arxiv.org/abs/1802.07426, 2018
52018
User service prediction in a communication network
V Verma, V Huang
US Patent App. 15/100,950, 2016
32016
Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Accuracy
A Lamb, V Verma, J Kannala, Y Bengio
arXiv preprint arXiv:1906.06784, 2019
22019
Modularity Matters: Learning Invariant Relational Reasoning Tasks
J Jo, V Verma, Y Bengio
arXiv preprint arXiv:1806.06765, 2018
22018
Towards understanding generalization via analytical learning theory
K Kawaguchi, Y Bengio, V Verma, LP Kaelbling
arXiv preprint arXiv:1802.07426, 2018
22018
GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning
V Verma, M Qu, A Lamb, Y Bengio, J Kannala, J Tang
arXiv preprint arXiv:1909.11715, 2019
12019
Towards understanding generalization in gradient-based meta-learning
S Guiroy, V Verma, C Pal
arXiv preprint arXiv:1907.07287, 2019
12019
SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks
A Lamb, S Ozair, V Verma, D Ha
arXiv preprint arXiv:1912.11570, 2019
2019
Interpolated Adversarial Training: Achieving Robust Neural Networks Without Sacrificing Too Much Accuracy
A Lamb, V Verma, J Kannala, Y Bengio
Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security …, 2019
2019
Identifying influence paths in a communication network
NH Kumar, R Balakrishnan, V Verma
US Patent 9,680,732, 2017
2017
Method and apparatus for determining similarity information for users of a network
V Verma
US Patent 9,373,128, 2016
2016
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