Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness

31 May 2019

Papers citing "Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness"

40 / 40 papers shown

Title
Dataset Distillation with Probabilistic Latent Features Zhe Li Sarah Cechnicka Cheng Ouyang Katharina Breininger Peter Schüffler Bernhard Kainz DD 47 0 0 10 May 2025
Subjective Logic Encodings Jake Vasilakes Chrysoula Zerva Sophia Ananiadou 48 0 0 17 Feb 2025
CoDiff: Conditional Diffusion Model for Collaborative 3D Object Detection zhe Huang Shuo Wang Yalin Wang Lei Wang DiffM 164 0 0 17 Feb 2025
Out-of-Distribution Detection using Synthetic Data Generation Momin Abbas Muneeza Azmat R. Horesh Mikhail Yurochkin 47 1 0 05 Feb 2025
Reducing Aleatoric and Epistemic Uncertainty through Multi-modal Data Acquisition Arthur Hoarau Benjamin Quost Sébastien Destercke Willem Waegeman UQCV UD PER 72 0 0 30 Jan 2025
Latent Space Chain-of-Embedding Enables Output-free LLM Self-Evaluation Yiming Wang Pei Zhang Baosong Yang Derek F. Wong Rui-cang Wang LRM 50 4 0 17 Oct 2024
Adversarial Safety-Critical Scenario Generation using Naturalistic Human Driving Priors Kunkun Hao Yonggang Luo Wen Cui Yuqiao Bai Jucheng Yang Songyang Yan Yuxi Pan Zijiang Yang AAML 33 17 0 06 Aug 2024
Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on Regression Xuanlong Yu Gianni Franchi Jindong Gu Emanuel Aldea UQCV 16 4 0 17 Aug 2023
Function-Space Regularization for Deep Bayesian Classification J. Lin Joe Watson Pascal Klink Jan Peters UQCV BDL 38 1 0 12 Jul 2023
Block-local learning with probabilistic latent representations David Kappel Khaleelulla Khan Nazeer Cabrel Teguemne Fokam Christian Mayr Anand Subramoney 24 4 0 24 May 2023
Non-Parametric Outlier Synthesis Leitian Tao Xuefeng Du Xiaojin Zhu Yixuan Li OODD 28 98 0 06 Mar 2023
Tailoring Language Generation Models under Total Variation Distance Haozhe Ji Pei Ke Zhipeng Hu Rongsheng Zhang Minlie Huang 28 18 0 26 Feb 2023
Post-hoc Uncertainty Learning using a Dirichlet Meta-Model Maohao Shen Yuheng Bu P. Sattigeri S. Ghosh Subhro Das G. Wornell UQCV OOD BDL 13 31 0 14 Dec 2022
Distribution-based Emotion Recognition in Conversation Wen Wu C. Zhang P. Woodland 24 4 0 09 Nov 2022
Quantifying Aleatoric and Epistemic Uncertainty in Machine Learning: Are Conditional Entropy and Mutual Information Appropriate Measures? Lisa Wimmer Yusuf Sale Paul Hofman Bern Bischl Eyke Hüllermeier PER UD 36 64 0 07 Sep 2022
OpenCon: Open-world Contrastive Learning Yiyou Sun Yixuan Li VLM SSL DRL 52 39 0 04 Aug 2022
Effective Out-of-Distribution Detection in Classifier Based on PEDCC-Loss Qiuyu Zhu Guohui Zheng Yingying Yan OODD 14 8 0 10 Apr 2022
Self-Distribution Distillation: Efficient Uncertainty Estimation Yassir Fathullah Mark J. F. Gales UQCV 19 11 0 15 Mar 2022
Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation Viktor Bengs Eyke Hüllermeier Willem Waegeman EDL UQCV UD 24 36 0 11 Mar 2022
Estimating the Uncertainty in Emotion Class Labels with Utterance-Specific Dirichlet Priors Wen Wu C. Zhang Xixin Wu P. Woodland 48 14 0 08 Mar 2022
Maximum Likelihood Uncertainty Estimation: Robustness to Outliers Deebul Nair Nico Hochgeschwender Miguel A. Olivares-Mendez OOD 30 7 0 03 Feb 2022
Improving robustness and calibration in ensembles with diversity regularization H. A. Mehrtens Camila González Anirban Mukhopadhyay UQCV 19 7 0 26 Jan 2022
Provable Guarantees for Understanding Out-of-distribution Detection Peyman Morteza Yixuan Li OODD 32 86 0 01 Dec 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification Maximilian Stadler Bertrand Charpentier Simon Geisler Daniel Zügner Stephan Günnemann UQCV BDL 41 80 0 26 Oct 2021
Generalized Out-of-Distribution Detection: A Survey Jingkang Yang Kaiyang Zhou Yixuan Li Ziwei Liu 188 879 0 21 Oct 2021
Deep Classifiers with Label Noise Modeling and Distance Awareness Vincent Fortuin Mark Collier F. Wenzel J. Allingham J. Liu Dustin Tran Balaji Lakshminarayanan Jesse Berent Rodolphe Jenatton E. Kokiopoulou UQCV 34 11 0 06 Oct 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 59 1,111 0 07 Jul 2021
Being a Bit Frequentist Improves Bayesian Neural Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 23 15 0 18 Jun 2021
Provably Robust Detection of Out-of-distribution Data (almost) for free Alexander Meinke Julian Bitterwolf Matthias Hein OODD 33 22 0 08 Jun 2021
DS-UI: Dual-Supervised Mixture of Gaussian Mixture Models for Uncertainty Inference Jiyang Xie Zhanyu Ma Jing-Hao Xue Guoqiang Zhang Jun Guo BDL 27 11 0 17 Nov 2020
Failure Prediction by Confidence Estimation of Uncertainty-Aware Dirichlet Networks Theodoros Tsiligkaridis UQCV 22 7 0 19 Oct 2020
Uncertainty in Gradient Boosting via Ensembles Aleksei Ustimenko Liudmila Prokhorenkova A. Malinin UQCV 28 94 0 18 Jun 2020
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts Bertrand Charpentier Daniel Zügner Stephan Günnemann UQCV UD EDL BDL 25 169 0 16 Jun 2020
Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data Yen-Chang Hsu Yilin Shen Hongxia Jin Z. Kira OODD 24 558 0 26 Feb 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 33 277 0 24 Feb 2020
Being Bayesian about Categorical Probability Taejong Joo U. Chung Minji Seo UQCV BDL 25 58 0 19 Feb 2020
Ensemble Distribution Distillation A. Malinin Bruno Mlodozeniec Mark J. F. Gales UQCV 27 230 0 30 Apr 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,837 0 08 Jul 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015