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09/18/2023
Unsupervised Open-Vocabulary Object Localization in Videos
In this paper, we show that recent advances in video representation lear...
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09/01/2023
Object-Centric Multiple Object Tracking
Unsupervised object-centric learning methods allow the partitioning of s...
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09/29/2022
Bridging the Gap to Real-World Object-Centric Learning
Humans naturally decompose their environment into entities at the approp...
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09/26/2022
Targeted Separation and Convergence with Kernel Discrepancies
Maximum mean discrepancies (MMDs) like the kernel Stein discrepancy (KSD...
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07/19/2022
Assaying Out-Of-Distribution Generalization in Transfer Learning
Since out-of-distribution generalization is a generally ill-posed proble...
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06/14/2021
PopSkipJump: Decision-Based Attack for Probabilistic Classifiers
Most current classifiers are vulnerable to adversarial examples, small i...
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06/16/2020
Metrizing Weak Convergence with Maximum Mean Discrepancies
Theorem 12 of Simon-Gabriel Schölkopf (JMLR, 2018) seemed to close a...
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02/05/2018
Adversarial Vulnerability of Neural Networks Increases With Input Dimension
Over the past four years, neural networks have proven vulnerable to adve...
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05/22/2017
From optimal transport to generative modeling: the VEGAN cookbook
We study unsupervised generative modeling in terms of the optimal transp...
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01/09/2017
AdaGAN: Boosting Generative Models
Generative Adversarial Networks (GAN) (Goodfellow et al., 2014) are an e...
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10/19/2016
Consistent Kernel Mean Estimation for Functions of Random Variables
We provide a theoretical foundation for non-parametric estimation of fun...
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04/18/2016
Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions
Kernel mean embeddings have recently attracted the attention of the mach...
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05/12/2015
