Search Results for author: Isay Katsman

Found 9 papers, 4 papers with code

Equivariant Manifold Flows

no code implementations19 Jul 2021 Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa

Tractably modelling distributions over manifolds has long been an important goal in the natural sciences.

Neural Manifold Ordinary Differential Equations

2 code implementations NeurIPS 2020 Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa

To better conform to data geometry, recent deep generative modelling techniques adapt Euclidean constructions to non-Euclidean spaces.

Density Estimation

Differentiating through the Fréchet Mean

2 code implementations ICML 2020 Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge Belongie, Ser-Nam Lim, Christopher De Sa

Recent advances in deep representation learning on Riemannian manifolds extend classical deep learning operations to better capture the geometry of the manifold.

Representation Learning

Enhancing Adversarial Example Transferability with an Intermediate Level Attack

1 code implementation ICCV 2019 Qian Huang, Isay Katsman, Horace He, Zeqi Gu, Serge Belongie, Ser-Nam Lim

We show that we can select a layer of the source model to perturb without any knowledge of the target models while achieving high transferability.

Fashion++: Minimal Edits for Outfit Improvement

no code implementations ICCV 2019 Wei-Lin Hsiao, Isay Katsman, Chao-yuan Wu, Devi Parikh, Kristen Grauman

We introduce Fashion++, an approach that proposes minimal adjustments to a full-body clothing outfit that will have maximal impact on its fashionability.

Image Generation

Adversarial Example Decomposition

no code implementations4 Dec 2018 Horace He, Aaron Lou, Qingxuan Jiang, Isay Katsman, Serge Belongie, Ser-Nam Lim

Research has shown that widely used deep neural networks are vulnerable to carefully crafted adversarial perturbations.

Semantic Segmentation with Scarce Data

no code implementations2 Jul 2018 Isay Katsman, Rohun Tripathi, Andreas Veit, Serge Belongie

Semantic segmentation is a challenging vision problem that usually necessitates the collection of large amounts of finely annotated data, which is often quite expensive to obtain.

Semantic Segmentation

Generative Adversarial Perturbations

1 code implementation CVPR 2018 Omid Poursaeed, Isay Katsman, Bicheng Gao, Serge Belongie

In this paper, we propose novel generative models for creating adversarial examples, slightly perturbed images resembling natural images but maliciously crafted to fool pre-trained models.

General Classification Semantic Segmentation

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