Ilya Tolstikhin
Ilya Tolstikhin
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TitleCited byYear
Wasserstein auto-encoders
I Tolstikhin, O Bousquet, S Gelly, B Schoelkopf
arXiv preprint arXiv:1711.01558, 2017
1182017
Adagan: Boosting generative models
IO Tolstikhin, S Gelly, O Bousquet, CJ Simon-Gabriel, B Schölkopf
Advances in Neural Information Processing Systems, 5424-5433, 2017
772017
Towards a learning theory of cause-effect inference
D Lopez-Paz, K Muandet, B Schölkopf, I Tolstikhin
International Conference on Machine Learning, 1452-1461, 2015
72*2015
From optimal transport to generative modeling: the VEGAN cookbook
O Bousquet, S Gelly, I Tolstikhin, CJ Simon-Gabriel, B Schoelkopf
arXiv preprint arXiv:1705.07642, 2017
382017
PAC-Bayes-empirical-Bernstein inequality
IO Tolstikhin, Y Seldin
Advances in Neural Information Processing Systems, 109-117, 2013
212013
Minimax estimation of kernel mean embeddings
I Tolstikhin, BK Sriperumbudur, K Muandet
The Journal of Machine Learning Research 18 (1), 3002-3048, 2017
162017
Localized complexities for transductive learning
I Tolstikhin, G Blanchard, M Kloft
Conference on Learning Theory, 857-884, 2014
122014
Minimax estimation of maximum mean discrepancy with radial kernels
IO Tolstikhin, BK Sriperumbudur, B Schölkopf
Advances in Neural Information Processing Systems, 1930-1938, 2016
72016
Permutational rademacher complexity
I Tolstikhin, N Zhivotovskiy, G Blanchard
International Conference on Algorithmic Learning Theory, 209-223, 2015
72015
On the Latent Space of Wasserstein Auto-Encoders
PK Rubenstein, B Schoelkopf, I Tolstikhin
arXiv preprint arXiv:1802.03761, 2018
62018
Clustering meets implicit generative models
F Locatello, D Vincent, I Tolstikhin, G Rätsch, S Gelly, B Schölkopf
arXiv preprint arXiv:1804.11130, 2018
32018
Differentially private database release via kernel mean embeddings
M Balog, I Tolstikhin, B Schölkopf
arXiv preprint arXiv:1710.01641, 2017
32017
Consistent kernel mean estimation for functions of random variables
CJ Simon-Gabriel, A Scibior, IO Tolstikhin, B Schölkopf
Advances in Neural Information Processing Systems, 1732-1740, 2016
32016
Concentration inequalities for samples without replacement
IO Tolstikhin
Theory of Probability & Its Applications 61 (3), 462-481, 2017
22017
Cover-based combinatorial bounds on probability of overfitting
AI Frey, IO Tolstikhin
Doklady Mathematics 89 (2), 185-187, 2014
22014
Wasserstein auto-encoders: Latent dimensionality and random encoders
PK Rubenstein, B Schoelkopf, I Tolstikhin
12018
Learning Disentangled Representations with Wasserstein Auto-Encoders
PK Rubenstein, B Schoelkopf, I Tolstikhin
12018
Probabilistic Active Learning of Functions in Structural Causal Models
PK Rubenstein, I Tolstikhin, P Hennig, B Schölkopf
arXiv preprint arXiv:1706.10234, 2017
12017
B0 matrix shim array design-optimization of the position, geometry and the number of segments of individual coil elements
I Zivkovic, I Tolstikhin, B Schölkopf, K Scheffler
12016
Minimax lower bounds for realizable transductive classification
I Tolstikhin, D Lopez-Paz
arXiv preprint arXiv:1602.03027, 2016
12016
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