Sliced-Wasserstein normalizing flows: beyond maximum likelihood training

12 July 2022

Papers citing "Sliced-Wasserstein normalizing flows: beyond maximum likelihood training"

7 / 7 papers shown

Title
Revisiting Sliced Wasserstein on Images: From Vectorization to Convolution Khai Nguyen Nhat Ho 56 25 0 04 Apr 2022
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 213 1,717 0 05 Dec 2019
Do Deep Generative Models Know What They Don't Know? Eric T. Nalisnick Akihiro Matsukawa Yee Whye Teh Dilan Görür Balaji Lakshminarayanan OOD 87 759 0 22 Oct 2018
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 305 3,144 0 09 Jul 2018
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 176 3,480 0 07 Oct 2016
Improved Techniques for Training GANs Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford Xi Chen GAN 486 9,073 0 10 Jun 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 277 3,722 0 26 May 2016