Uncertainty in the Variational Information Bottleneck

2 July 2018

Papers citing "Uncertainty in the Variational Information Bottleneck"

27 / 27 papers shown

Title
Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation Pei Liu Luping Ji EDL 29 4 0 07 May 2024
Planning to Go Out-of-Distribution in Offline-to-Online Reinforcement Learning Trevor A. McInroe Adam Jelley Stefano V. Albrecht Amos Storkey OffRL OnRL 28 6 0 09 Oct 2023
Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHS Rishabh Singh José C. Príncipe UQCV 39 3 0 03 Nov 2022
Latent Discriminant deterministic Uncertainty Gianni Franchi Xuanlong Yu Andrei Bursuc Emanuel Aldea Séverine Dubuisson David Filliat UQCV 24 18 0 20 Jul 2022
GSMFlow: Generation Shifts Mitigating Flow for Generalized Zero-Shot Learning Zhi Chen Yadan Luo Sen Wang Jingjing Li Zi Huang 21 14 0 05 Jul 2022
Bounds all around: training energy-based models with bidirectional bounds Cong Geng Jia Wang Zhiyong Gao J. Frellsen Søren Hauberg 24 15 0 01 Nov 2021
Unsupervised Class-Incremental Learning Through Confusion Shivam Khare Kun Cao James M. Rehg SSL CLL 24 6 0 09 Apr 2021
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation Alexandre Ramé Matthieu Cord FedML 53 51 0 14 Jan 2021
TabTransformer: Tabular Data Modeling Using Contextual Embeddings Xin Huang A. Khetan Milan Cvitkovic Zohar Karnin ViT LMTD 157 420 0 11 Dec 2020
The Hidden Uncertainty in a Neural Networks Activations Janis Postels Hermann Blum Yannick Strümpler Cesar Cadena Roland Siegwart Luc Van Gool Federico Tombari UQCV 32 22 0 05 Dec 2020
Further Analysis of Outlier Detection with Deep Generative Models Ziyu Wang Bin Dai David Wipf Jun Zhu 17 39 0 25 Oct 2020
Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness Long Zhao Ting Liu Xi Peng Dimitris N. Metaxas OOD AAML 27 165 0 15 Oct 2020
Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution Settings John Mitros A. Pakrashi Brian Mac Namee UQCV 26 2 0 03 Sep 2020
Detecting Out-of-distribution Samples via Variational Auto-encoder with Reliable Uncertainty Estimation Xuming Ran Mingkun Xu Lingrui Mei Qi Xu Quanying Liu OODD UQCV 42 50 0 16 Jul 2020
Density of States Estimation for Out-of-Distribution Detection Warren Morningstar Cusuh Ham Andrew Gallagher Balaji Lakshminarayanan Alexander A. Alemi Joshua V. Dillon OODD 22 83 0 16 Jun 2020
Probabilistic Autoencoder Vanessa Böhm U. Seljak UQCV BDL DRL 24 32 0 09 Jun 2020
Mutual Information Gradient Estimation for Representation Learning Liangjiang Wen Yiji Zhou Lirong He Mingyuan Zhou Zenglin Xu DRL SSL 33 27 0 03 May 2020
The Conditional Entropy Bottleneck Ian S. Fischer OOD 27 115 0 13 Feb 2020
Likelihood Ratios for Out-of-Distribution Detection Jie Jessie Ren Peter J. Liu Emily Fertig Jasper Snoek Ryan Poplin M. DePristo Joshua V. Dillon Balaji Lakshminarayanan OODD 50 716 0 07 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 29 1,658 0 06 Jun 2019
Minimal Achievable Sufficient Statistic Learning Milan Cvitkovic Günther Koliander 25 12 0 19 May 2019
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift Stephan Rabanser Stephan Günnemann Zachary Chase Lipton 33 359 0 29 Oct 2018
WAIC, but Why? Generative Ensembles for Robust Anomaly Detection Hyun-Jae Choi Eric Jang Alexander A. Alemi OODD 20 82 0 02 Oct 2018
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks Lechao Xiao Yasaman Bahri Jascha Narain Sohl-Dickstein S. Schoenholz Jeffrey Pennington 244 349 0 14 Jun 2018
Learning Representations for Neural Network-Based Classification Using the Information Bottleneck Principle Rana Ali Amjad Bernhard C. Geiger 35 195 0 27 Feb 2018
Nonlinear Information Bottleneck Artemy Kolchinsky Brendan D. Tracey David Wolpert 17 153 0 06 May 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,675 0 05 Dec 2016