activity
20182020
most citedNeural Manifold Ordinary Differential Equations

26 citations · 26 across the 1 of their papers we have counts for

collaborators

6 papers

stat.ML202026 cited

Neural Manifold Ordinary Differential Equations

Aaron Lou, Derek Lim, Isay Katsman +4

To better conform to data geometry, recent deep generative modelling techniques adapt Euclidean constructions to non-Euclidean spaces. In this paper, we study normalizing flows on…

cs.LG2019

Enhancing Adversarial Example Transferability with an Intermediate Level Attack

Qian Huang, Isay Katsman, Horace He +3

Neural networks are vulnerable to adversarial examples, malicious inputs crafted to fool trained models. Adversarial examples often exhibit black-box transfer, meaning that adversa…

cs.CV2019

Fashion++: Minimal Edits for Outfit Improvement

Wei-Lin Hsiao, Isay Katsman, Chao-Yuan Wu +2

Given an outfit, what small changes would most improve its fashionability? This question presents an intriguing new vision challenge. We introduce Fashion++, an approach that propo…

stat.ML2018

Adversarial Example Decomposition

Horace He, Aaron Lou, Qingxuan Jiang +3

Research has shown that widely used deep neural networks are vulnerable to carefully crafted adversarial perturbations. Moreover, these adversarial perturbations often transfer acr…

cs.LG2018

Intermediate Level Adversarial Attack for Enhanced Transferability

Qian Huang, Zeqi Gu, Isay Katsman +5

Neural networks are vulnerable to adversarial examples, malicious inputs crafted to fool trained models. Adversarial examples often exhibit black-box transfer, meaning that adversa…

cs.CV2018

Semantic Segmentation with Scarce Data

Isay Katsman, Rohun Tripathi, Andreas Veit +1

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.…