Uncertainty in the Variational Information Bottleneck

2 July 2018

Papers citing "Uncertainty in the Variational Information Bottleneck"

50 / 69 papers shown

Title
Information-Theoretic Reward Modeling for Stable RLHF: Detecting and Mitigating Reward Hacking Yuchun Miao Liang Ding Sen Zhang Rong Bao L. Zhang Dacheng Tao 172 0 0 15 Oct 2025
Label Smoothing is a Pragmatic Information Bottleneck Sota Kudo 111 0 0 12 Aug 2025
Handling Out-of-Distribution Data: A SurveyIEEE Transactions on Knowledge and Data Engineering (TKDE), 2025 L. Tamang Mohamed Reda Bouadjenek Richard Dazeley S. Aryal OOD OODD 274 4 0 25 Jul 2025
Exploring bidirectional bounds for minimax-training of Energy-based modelsInternational Journal of Computer Vision (IJCV), 2025 Cong Geng Jia Wang Li Chen Zhiyong Gao J. Frellsen Søren Hauberg 266 0 0 05 Jun 2025
Epistemic Artificial Intelligence is Essential for Machine Learning Models to Truly 'Know When They Do Not Know' Shireen Kudukkil Manchingal Andrew Bradley Julian F. P. Kooij Keivan K1 Shariatmadar Neil Yorke-Smith Fabio Cuzzolin 529 1 0 08 May 2025
Mitigating Hallucinations in Large Vision-Language Models by Adaptively Constraining Information FlowAAAI Conference on Artificial Intelligence (AAAI), 2025 Jiaqi Bai Hongcheng Guo Zhongyuan Peng Zhiqiang Wang Zhiyu Li Mingze Li Zhihong Tian VLM 208 6 0 28 Feb 2025
Forte : Finding Outliers with Representation Typicality EstimationInternational Conference on Learning Representations (ICLR), 2024 Debargha Ganguly Warren Morningstar A. Yu Vipin Chaudhary OODD 232 4 0 02 Oct 2024
Resultant: Incremental Effectiveness on Likelihood for Unsupervised Out-of-Distribution Detection Yewen Li Chaojie Wang Xiaobo Xia Xu He Ruyi An Dong Li Tongliang Liu Bo An Xinrun Wang OODD 208 0 0 05 Sep 2024
A Rate-Distortion View of Uncertainty Quantification Ifigeneia Apostolopoulou Benjamin Eysenbach Frank Nielsen Artur Dubrawski UQCV 385 3 0 16 Jun 2024
Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation Pei Liu Luping Ji EDL 326 6 0 07 May 2024
Cell Variational Information Bottleneck Network Zhonghua Zhai Chen Ju Jinsong Lan Shuai Xiao 253 0 0 22 Mar 2024
Masked Gamma-SSL: Learning Uncertainty Estimation via Masked Image Modeling David S. W. Williams Matthew Gadd Paul Newman Daniele De Martini UQCV 107 1 0 27 Feb 2024
Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods Jiaxin Zhang Kamalika Das Kumar Sricharan UQCV 153 2 0 20 Feb 2024
Flexible Variational Information Bottleneck: Achieving Diverse Compression with a Single Training Sota Kudo N. Ono Shigehiko Kanaya Ming Huang 160 3 0 02 Feb 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 251 7 0 09 Oct 2023
IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learningJournal of Computational Physics (JCP), 2023 Ling Guo Hao Wu Wenwen Zhou Yan Wang Tao Zhou UQCV 292 21 0 07 Feb 2023
Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHS Rishabh Singh José C. Príncipe UQCV 159 3 0 03 Nov 2022
Latent Discriminant deterministic UncertaintyEuropean Conference on Computer Vision (ECCV), 2022 Gianni Franchi Xuanlong Yu Andrei Bursuc Emanuel Aldea Séverine Dubuisson David Filliat UQCV 194 18 0 20 Jul 2022
GSMFlow: Generation Shifts Mitigating Flow for Generalized Zero-Shot LearningIEEE transactions on multimedia (IEEE TMM), 2022 Zhi Chen Yadan Luo Sen Wang Jingjing Li Zi Huang 216 18 0 05 Jul 2022
InfoAT: Improving Adversarial Training Using the Information Bottleneck PrincipleIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022 Mengting Xu Tao Zhang Zhongnian Li Daoqiang Zhang AAML 117 20 0 23 Jun 2022
Posterior Refinement Improves Sample Efficiency in Bayesian Neural NetworksNeural Information Processing Systems (NeurIPS), 2022 Agustinus Kristiadi Runa Eschenhagen Philipp Hennig BDL 210 15 0 20 May 2022
Bayesian Imitation Learning for End-to-End Mobile ManipulationInternational Conference on Machine Learning (ICML), 2022 Yuqing Du Daniel Ho Alexander A. Alemi Eric Jang Mohi Khansari SSL 127 13 0 15 Feb 2022
From Psychological Curiosity to Artificial Curiosity: Curiosity-Driven Learning in Artificial Intelligence Tasks Chenyu Sun Hangwei Qian Chunyan Miao 192 13 0 20 Jan 2022
Competing Mutual Information Constraints with Stochastic Competition-based Activations for Learning Diversified RepresentationsAAAI Conference on Artificial Intelligence (AAAI), 2022 Konstantinos P. Panousis A. Antoniadis S. Chatzis 245 5 0 10 Jan 2022
The Exponentially Tilted Gaussian Prior for Variational Autoencoders Griffin Floto Stefan Kremer Mihai Nica DRL 127 1 0 30 Nov 2021
Bounds all around: training energy-based models with bidirectional boundsNeural Information Processing Systems (NeurIPS), 2021 Cong Geng Jia Wang Zhiyong Gao J. Frellsen Søren Hauberg 325 17 0 01 Nov 2021
Information Theoretic Structured Generative Modeling Bo Hu Shujian Yu José C. Príncipe SyDa DRL 145 0 0 12 Oct 2021
On the Out-of-distribution Generalization of Probabilistic Image Modelling Mingtian Zhang Andi Zhang Jingyu Sun OODD 354 49 0 04 Sep 2021
DOI: Divergence-based Out-of-Distribution Indicators via Deep Generative Models Wenxiao Chen Xiaohui Nie Mingliang Li Dan Pei OODD 117 1 0 12 Aug 2021
On the Practicality of Deterministic Epistemic Uncertainty Janis Postels Mattia Segu Tao Sun Luca Sieber Luc Van Gool Feng Yu Federico Tombari UQCV 359 69 0 01 Jul 2021
Rectangular Flows for Manifold LearningNeural Information Processing Systems (NeurIPS), 2021 M. Volkovs Gabriel Loaiza-Ganem Geoff Pleiss John P. Cunningham DRL 297 51 0 02 Jun 2021
Deconvolutional Density Network: Modeling Free-Form Conditional DistributionsAAAI Conference on Artificial Intelligence (AAAI), 2021 Bing Chen Mazharul Islam Jisuo Gao Lin Wang BDL CML 237 8 0 29 May 2021
Self-Paced Uncertainty Estimation for One-shot Person Re-Identification Yulin Zhang Bo Ma Longyao Liu Xin Yi 143 2 0 19 Apr 2021
Unsupervised Class-Incremental Learning Through Confusion Shivam Khare Kun Cao James M. Rehg SSL CLL 198 7 0 09 Apr 2021
Hierarchical VAEs Know What They Don't KnowInternational Conference on Machine Learning (ICML), 2021 Jakob Drachmann Havtorn J. Frellsen Søren Hauberg Lars Maaløe DRL 585 82 0 16 Feb 2021
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial EstimationInternational Conference on Learning Representations (ICLR), 2021 Alexandre Ramé Matthieu Cord FedML 223 58 0 14 Jan 2021
Disentangled Information BottleneckAAAI Conference on Artificial Intelligence (AAAI), 2020 Ziqi Pan Li Niu Jianfu Zhang Liqing Zhang 182 47 0 14 Dec 2020
TabTransformer: Tabular Data Modeling Using Contextual Embeddings Xin Huang A. Khetan Milan Cvitkovic Zohar Karnin ViT LMTD 372 613 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 461 24 0 05 Dec 2020
Interpretable Signed Link Prediction with Signed Infomax Hyperbolic GraphIEEE Transactions on Knowledge and Data Engineering (TKDE), 2020 Yadan Luo Zi Huang Hongxu Chen Yang Yang Mahsa Baktash 184 13 0 25 Nov 2020
Bottleneck Problems: Information and Estimation-Theoretic View S. Asoodeh Flavio du Pin Calmon 160 18 0 12 Nov 2020
Further Analysis of Outlier Detection with Deep Generative ModelsNeural Information Processing Systems (NeurIPS), 2020 Ziyu Wang Bin Dai David Wipf Jun Zhu 189 41 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 404 182 0 15 Oct 2020
An Algorithm for Out-Of-Distribution Attack to Neural Network Encoder Liang Liang Linhai Ma Linchen Qian Jiasong Chen OODD 238 2 0 17 Sep 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 276 2 0 03 Sep 2020
Detecting Out-of-distribution Samples via Variational Auto-encoder with Reliable Uncertainty EstimationNeural Networks (NN), 2020 Xuming Ran Mingkun Xu Lingrui Mei Qi Xu Quanying Liu OODD UQCV 258 59 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 268 93 0 16 Jun 2020
Revisiting Explicit Regularization in Neural Networks for Well-Calibrated Predictive Uncertainty Taejong Joo U. Chung BDL UQCV 226 0 0 11 Jun 2020
Probabilistic Autoencoder Vanessa Böhm U. Seljak UQCV BDL DRL 217 32 0 09 Jun 2020
Mutual Information Gradient Estimation for Representation LearningInternational Conference on Learning Representations (ICLR), 2020 Liangjiang Wen Yiji Zhou Lirong He Mingyuan Zhou Zenglin Xu DRL SSL 277 34 0 03 May 2020