Deep Variational Information Bottleneck

1 December 2016

Papers citing "Deep Variational Information Bottleneck"

50 / 348 papers shown

Title
Measuring the Biases and Effectiveness of Content-Style Disentanglement Xiao Liu Spyridon Thermos Gabriele Valvano A. Chartsias Alison Q. OÑeil Sotirios A. Tsaftaris CoGe DRL 34 18 0 27 Aug 2020
Whitening and second order optimization both make information in the dataset unusable during training, and can reduce or prevent generalization Neha S. Wadia Daniel Duckworth S. Schoenholz Ethan Dyer Jascha Narain Sohl-Dickstein 31 13 0 17 Aug 2020
Evaluating Lossy Compression Rates of Deep Generative Models Sicong Huang Alireza Makhzani Yanshuai Cao Roger C. Grosse EGVM DRL 8 27 0 15 Aug 2020
When is invariance useful in an Out-of-Distribution Generalization problem ? Masanori Koyama Shoichiro Yamaguchi OOD 36 65 0 04 Aug 2020
Improving Generalization in Meta-learning via Task Augmentation Huaxiu Yao Long-Kai Huang Linjun Zhang Ying Wei Li Tian James Zou Junzhou Huang Z. Li 50 81 0 26 Jul 2020
End-to-end Learning of Compressible Features Saurabh Singh Sami Abu-El-Haija Nick Johnston Johannes Ballé Abhinav Shrivastava G. Toderici SSL 99 71 0 23 Jul 2020
Adversarial Training Reduces Information and Improves Transferability M. Terzi Alessandro Achille Marco Maggipinto Gian Antonio Susto AAML 24 23 0 22 Jul 2020
Learning to Learn with Variational Information Bottleneck for Domain Generalization Yingjun Du Jun Xu Huan Xiong Qiang Qiu Xiantong Zhen Cees G. M. Snoek Ling Shao BDL OOD 30 164 0 15 Jul 2020
Towards a Theoretical Understanding of the Robustness of Variational Autoencoders A. Camuto M. Willetts Stephen J. Roberts Chris Holmes Tom Rainforth AAML DRL 29 30 0 14 Jul 2020
Efficient Empowerment Estimation for Unsupervised Stabilization Ruihan Zhao Kevin Lu Pieter Abbeel Stas Tiomkin 32 8 0 14 Jul 2020
AUTO3D: Novel view synthesis through unsupervisely learned variational viewpoint and global 3D representation Xiaofeng Liu Tong Che Yiqun Lu Chao Yang Site Li J. You 3DV 48 21 0 13 Jul 2020
Meta-Learning Requires Meta-Augmentation Janarthanan Rajendran A. Irpan Eric Jang 29 93 0 10 Jul 2020
Robust Classification under Class-Dependent Domain Shift T. Galstyan Hrant Khachatrian Greg Ver Steeg Aram Galstyan OOD 16 2 0 10 Jul 2020
Auxiliary Learning by Implicit Differentiation Aviv Navon Idan Achituve Haggai Maron Gal Chechik Ethan Fetaya 33 59 0 22 Jun 2020
Contrastive Learning for Weakly Supervised Phrase Grounding Tanmay Gupta Arash Vahdat Gal Chechik Xiaodong Yang Jan Kautz Derek Hoiem ObjD SSL 44 141 0 17 Jun 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 24 84 0 16 Jun 2020
Learning the Redundancy-free Features for Generalized Zero-Shot Object Recognition Zongyan Han Zhenyong Fu Jian Yang 23 86 0 16 Jun 2020
Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks Roman Pogodin P. Latham 27 34 0 12 Jun 2020
A Variational Approach to Privacy and Fairness Borja Rodríguez Gálvez Ragnar Thobaben Mikael Skoglund FaML DRL 19 25 0 11 Jun 2020
On the Maximum Mutual Information Capacity of Neural Architectures Brandon Foggo Nan Yu TPM 29 3 0 10 Jun 2020
Probabilistic Autoencoder Vanessa Böhm U. Seljak UQCV BDL DRL 24 32 0 09 Jun 2020
Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement Xiaojie Guo Liang Zhao Zhao Qin Lingfei Wu Amarda Shehu Yanfang Ye CoGe DRL 43 46 0 09 Jun 2020
What Makes for Good Views for Contrastive Learning? Yonglong Tian Chen Sun Ben Poole Dilip Krishnan Cordelia Schmid Phillip Isola SSL 39 1,308 0 20 May 2020
Learning and Inference in Imaginary Noise Models Saeed Saremi BDL DRL 11 2 0 18 May 2020
Robust Training of Vector Quantized Bottleneck Models A. Lancucki J. Chorowski Guillaume Sanchez R. Marxer Nanxin Chen Hans J. G. A. Dolfing Sameer Khurana Tanel Alumäe Antoine Laurent 29 58 0 18 May 2020
Attentional Bottleneck: Towards an Interpretable Deep Driving Network Jinkyu Kim Mayank Bansal 27 13 0 08 May 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
A Batch Normalized Inference Network Keeps the KL Vanishing Away Qile Zhu Jianlin Su Wei Bi Xiaojiang Liu Xiyao Ma Xiaolin Li D. Wu BDL DRL 42 61 0 27 Apr 2020
Generating Tertiary Protein Structures via an Interpretative Variational Autoencoder Xiaojie Guo Yuanqi Du Sivani Tadepalli Liang Zhao Amarda Shehu DRL 30 26 0 08 Apr 2020
Learning Agile Robotic Locomotion Skills by Imitating Animals Xue Bin Peng Erwin Coumans Tingnan Zhang T. Lee Jie Tan Sergey Levine 34 499 0 02 Apr 2020
Unpacking Information Bottlenecks: Unifying Information-Theoretic Objectives in Deep Learning Andreas Kirsch Clare Lyle Y. Gal 27 16 0 27 Mar 2020
On Information Plane Analyses of Neural Network Classifiers -- A Review Bernhard C. Geiger 32 50 0 21 Mar 2020
ROMA: Multi-Agent Reinforcement Learning with Emergent Roles Tonghan Wang Heng Dong V. Lesser Chongjie Zhang 57 212 0 18 Mar 2020
What Information Does a ResNet Compress? L. N. Darlow Amos Storkey SSL 32 11 0 13 Mar 2020
Continuous Domain Adaptation with Variational Domain-Agnostic Feature Replay Qicheng Lao Xiang Jiang Mohammad Havaei Yoshua Bengio VLM 23 33 0 09 Mar 2020
The Variational InfoMax Learning Objective Vincenzo Crescimanna Bruce P. Graham 23 0 0 07 Mar 2020
NestedVAE: Isolating Common Factors via Weak Supervision M. Vowels Necati Cihan Camgöz Richard Bowden CML DRL 26 21 0 26 Feb 2020
CEB Improves Model Robustness Ian S. Fischer Alexander A. Alemi AAML 19 28 0 13 Feb 2020
The Conditional Entropy Bottleneck Ian S. Fischer OOD 29 116 0 13 Feb 2020
Deep Representation Learning in Speech Processing: Challenges, Recent Advances, and Future Trends S. Latif R. Rana Sara Khalifa Raja Jurdak Junaid Qadir Björn W. Schuller AI4TS 37 81 0 02 Jan 2020
Independence Promoted Graph Disentangled Networks Yanbei Liu Tianlin Li Shu Wu Zhitao Xiao 30 94 0 26 Nov 2019
Improving Unsupervised Domain Adaptation with Variational Information Bottleneck Yuxuan Song Lantao Yu Zhangjie Cao Zhiming Zhou Jian Shen Shuo Shao Weinan Zhang Yong Yu 31 17 0 21 Nov 2019
Information in Infinite Ensembles of Infinitely-Wide Neural Networks Ravid Shwartz-Ziv Alexander A. Alemi 27 21 0 20 Nov 2019
Learning Representations in Reinforcement Learning:An Information Bottleneck Approach Yingjun Pei Xinwen Hou SSL 39 10 0 12 Nov 2019
Disentangle, align and fuse for multimodal and semi-supervised image segmentation A. Chartsias G. Papanastasiou Chengjia Wang S. Semple D. Newby R. Dharmakumar Sotirios A. Tsaftaris 24 13 0 11 Nov 2019
Enhancing VAEs for Collaborative Filtering: Flexible Priors & Gating Mechanisms Daeryong Kim B. Suh 24 50 0 03 Nov 2019
Understanding the Limitations of Variational Mutual Information Estimators Jiaming Song Stefano Ermon SSL DRL 25 202 0 14 Oct 2019
Learning Nearly Decomposable Value Functions Via Communication Minimization Tonghan Wang Jianhao Wang Chongyi Zheng Chongjie Zhang 23 133 0 11 Oct 2019
Predicting with High Correlation Features Devansh Arpit Caiming Xiong R. Socher OODD OOD 19 7 0 01 Oct 2019
Multi-mapping Image-to-Image Translation via Learning Disentanglement Xiaoming Yu Yuanqi Chen Thomas H. Li Shan Liu Ge Li DRL 25 104 0 17 Sep 2019