1.4k citations · 2.1k across the 21 of their papers we have counts for
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Wasserstein Auto-Encoders
Ilya Tolstikhin, Olivier Bousquet, Sylvain Gelly +1
We propose the Wasserstein Auto-Encoder (WAE)---a new algorithm for building a generative model of the data distribution. WAE minimizes a penalized form of the Wasserstein distance…
Differentially Private Database Release via Kernel Mean Embeddings
Matej Balog, Ilya Tolstikhin, Bernhard Schölkopf
We lay theoretical foundations for new database release mechanisms that allow third-parties to construct consistent estimators of population statistics, while ensuring that the pri…
Probabilistic Active Learning of Functions in Structural Causal Models
Paul K. Rubenstein, Ilya Tolstikhin, Philipp Hennig +1
We consider the problem of learning the functions computing children from parents in a Structural Causal Model once the underlying causal graph has been identified. This is in some…
From optimal transport to generative modeling: the VEGAN cookbook
Olivier Bousquet, Sylvain Gelly, Ilya Tolstikhin +2
We study unsupervised generative modeling in terms of the optimal transport (OT) problem between true (but unknown) data distribution and the latent variable model distributi…
AdaGAN: Boosting Generative Models
Ilya Tolstikhin, Sylvain Gelly, Olivier Bousquet +2
Generative Adversarial Networks (GAN) (Goodfellow et al., 2014) are an effective method for training generative models of complex data such as natural images. However, they are not…