Yuxuan Zhou

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Common Coauthors
Commonly Cited References
Action Title Year Authors # of times referenced
+ PDF Chat Deep Learning Face Attributes in the Wild 2015 Ziwei Liu
Ping Luo
Xiaogang Wang
Xiaoou Tang
1
+ Density estimation using Real NVP 2016 Laurent Dinh
Jascha Sohl‐Dickstein
Samy Bengio
1
+ A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks 2016 Dan Hendrycks
Kevin Gimpel
1
+ A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks 2018 Kimin Lee
Kibok Lee
Honglak Lee
Jinwoo Shin
1
+ Deep Anomaly Detection with Outlier Exposure 2018 Dan Hendrycks
Mantas Mazeika
Thomas G. Dietterich
1
+ Understanding the (un)interpretability of natural image distributions using generative models 2019 Ryen Krusinga
Sohil Shah
Matthias Zwicker
Tom Goldstein
David W. Jacobs
1
+ OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations 2019 Pramuditha Perera
Ramesh Nallapati
Bing Xiang
1
+ PDF Chat Latent Space Autoregression for Novelty Detection 2019 Davide Abati
Angelo Porrello
Simone Calderara
Rita Cucchiara
1
+ Deep Semi-Supervised Anomaly Detection 2019 Lukas Ruff
Robert A. Vandermeulen
Nico Görnitz
Alexander Binder
Emmanuel MĂŒller
Klaus‐Robert MĂŒller
Marius Kloft
1
+ Detecting Out-of-Distribution Inputs to Deep Generative Models Using a Test for Typicality. 2019 Eric Nalisnick
Akihiro Matsukawa
Yee Whye Teh
Balaji Lakshminarayanan
1
+ Out-of-Distribution Detection Using Neural Rendering Generative Models 2019 Yujia Huang
Sihui Dai
Tan M. Nguyen
Richard G. Baraniuk
Anima Anandkumar
1
+ Glow: Generative Flow with Invertible 1x1 Convolutions 2018 Diederik P. Kingma
Prafulla Dhariwal
1
+ Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples 2017 Kimin Lee
Honglak Lee
Kibok Lee
Jinwoo Shin
1
+ Do Deep Generative Models Know What They Don't Know? 2018 Eric Nalisnick
Akihiro Matsukawa
Yee Whye Teh
Dilan GörĂŒr
Balaji Lakshminarayanan
1
+ Deep Anomaly Detection Using Geometric Transformations 2018 Izhak Golan
Ran El‐Yaniv
1
+ A note on the evaluation of generative models 2015 Lucas Theis
AĂ€ron van den Oord
Matthias Bethge
1
+ Likelihood Ratios for Out-of-Distribution Detection 2019 Jie Ren
Peter J. Liu
Emily Fertig
Jasper Snoek
Ryan Poplin
Mark A. DePristo
Joshua V. Dillon
Balaji Lakshminarayanan
1
+ Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models 2019 Tong Che
Xiaofeng Liu
Site Li
Yubin Ge
Ruixiang Zhang
Caiming Xiong
Yoshua Bengio
1
+ Input complexity and out-of-distribution detection with likelihood-based generative models 2019 Joan SerrĂ 
David Álvarez
Vicenç Gómez
Olga Slizovskaia
JosĂ© F. NĂșñez
Jordi Luque
1
+ Classification-Based Anomaly Detection for General Data 2020 Liron Bergman
Yedid Hoshen
1
+ Rethinking Assumptions in Deep Anomaly Detection 2020 Lukas Ruff
Robert A. Vandermeulen
Billy Joe Franks
Klaus‐Robert MĂŒller
Marius Kloft
1
+ Contrastive Training for Improved Out-of-Distribution Detection. 2020 Jim Winkens
Rudy Bunel
Abhijit Guha Roy
Robert Stanforth
Vivek Natarajan
Joseph R. Ledsam
Patricia MacWilliams
Pushmeet Kohli
Alan Karthikesalingam
Simon Kohl
1
+ LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop 2015 Fisher Yu
Yinda Zhang
Shuran Song
Ari Seff
Jianxiong Xiao
1