Search Results for author: Aaron Lou

Found 4 papers, 2 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

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.

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