Opening the Black Box of Deep Neural Networks via Information

2 March 2017

Papers citing "Opening the Black Box of Deep Neural Networks via Information"

50 / 188 papers shown

Title
Adaptation of Autoencoder for Sparsity Reduction From Clinical Notes Representation Learning Thanh-Dung Le R. Noumeir J. Rambaud Guillaume Sans P. Jouvet 30 7 0 26 Sep 2022
Graph Contrastive Learning with Cross-view Reconstruction Qianlong Wen Z. Ouyang Chunhui Zhang Y. Qian Yanfang Ye Chuxu Zhang SSL 20 6 0 16 Sep 2022
Enhancing Deep Learning Performance of Massive MIMO CSI Feedback Sijie Ji Mo Li 11 6 0 24 Aug 2022
Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis Xuanyuan Han Pietro Barbiero Dobrik Georgiev Lucie Charlotte Magister Pietro Lió MILM 34 41 0 22 Aug 2022
CoShNet: A Hybrid Complex Valued Neural Network using Shearlets Manny Ko Ujjawal K. Panchal Héctor Andrade-Loarca Andres Mendez-Vazquez 25 1 0 14 Aug 2022
Statistical Hypothesis Testing Based on Machine Learning: Large Deviations Analysis P. Braca L. Millefiori A. Aubry S. Maranò A. De Maio P. Willett 29 12 0 22 Jul 2022
Green, Quantized Federated Learning over Wireless Networks: An Energy-Efficient Design Minsu Kim Walid Saad Mohammad Mozaffari Merouane Debbah FedML MQ 18 27 0 19 Jul 2022
One Model to Unite Them All: Personalized Federated Learning of Multi-Contrast MRI Synthesis Onat Dalmaz Muhammad Usama Mirza Gokberk Elmas Muzaffer Özbey S. Dar Emir Ceyani Salman Avestimehr Tolga cCukur MedIm 28 39 0 13 Jul 2022
On Leave-One-Out Conditional Mutual Information For Generalization Mohamad Rida Rammal Alessandro Achille Aditya Golatkar Suhas Diggavi Stefano Soatto VLM 28 5 0 01 Jul 2022
Learning sparse features can lead to overfitting in neural networks Leonardo Petrini Francesco Cagnetta Eric Vanden-Eijnden M. Wyart MLT 34 23 0 24 Jun 2022
Explanation-based Counterfactual Retraining(XCR): A Calibration Method for Black-box Models Liu Zhendong Wenyu Jiang Yan Zhang Chongjun Wang CML 6 0 0 22 Jun 2022
Interpretable machine learning optimization (InterOpt) for operational parameters: a case study of highly-efficient shale gas development Yuntian Chen Dong-juan Zhang Qun Zhao D. Liu 11 6 0 20 Jun 2022
A Functional Information Perspective on Model Interpretation Itai Gat Nitay Calderon Roi Reichart Tamir Hazan AAML FAtt 33 6 0 12 Jun 2022
Batch Normalization Is Blind to the First and Second Derivatives of the Loss Zhanpeng Zhou Wen Shen Huixin Chen Ling Tang Quanshi Zhang 34 2 0 30 May 2022
Gacs-Korner Common Information Variational Autoencoder Michael Kleinman Alessandro Achille Stefano Soatto J. Kao CML DRL 24 12 0 24 May 2022
Gaussian Pre-Activations in Neural Networks: Myth or Reality? Pierre Wolinski Julyan Arbel AI4CE 68 8 0 24 May 2022
Discovering and Explaining the Representation Bottleneck of Graph Neural Networks from Multi-order Interactions Fang Wu Siyuan Li Lirong Wu Dragomir R. Radev Stan Z. Li 27 2 0 15 May 2022
Mutual information estimation for graph convolutional neural networks Marius Cervera Landsverk S. Riemer-Sørensen SSL GNN 22 1 0 31 Mar 2022
Information-Theoretic Odometry Learning Sen Zhang Jing Zhang Dacheng Tao 15 5 0 11 Mar 2022
Discriminability-Transferability Trade-Off: An Information-Theoretic Perspective Quan Cui Bingchen Zhao Zhao-Min Chen Borui Zhao Renjie Song Jiajun Liang Boyan Zhou Osamu Yoshie 24 18 0 08 Mar 2022
Resolving label uncertainty with implicit posterior models Esther Rolf Nikolay Malkin Alexandros Graikos A. Jojic Caleb Robinson Nebojsa Jojic UQCV 26 10 0 28 Feb 2022
HRel: Filter Pruning based on High Relevance between Activation Maps and Class Labels C. Sarvani Mrinmoy Ghorai S. Dubey S. H. Shabbeer Basha VLM 32 37 0 22 Feb 2022
Fortuitous Forgetting in Connectionist Networks Hattie Zhou Ankit Vani Hugo Larochelle Aaron Courville CLL 11 42 0 01 Feb 2022
Extracting Finite Automata from RNNs Using State Merging William Merrill Nikolaos Tsilivis 15 14 0 28 Jan 2022
Overview frequency principle/spectral bias in deep learning Z. Xu Yaoyu Zhang Tao Luo FaML 30 65 0 19 Jan 2022
Real-World Graph Convolution Networks (RW-GCNs) for Action Recognition in Smart Video Surveillance Justin Sanchez Christopher Neff Hamed Tabkhi GNN 30 9 0 15 Jan 2022
Optimal Representations for Covariate Shift Yangjun Ruan Yann Dubois Chris J. Maddison OOD 25 68 0 31 Dec 2021
Separation of Scales and a Thermodynamic Description of Feature Learning in Some CNNs Inbar Seroussi Gadi Naveh Z. Ringel 30 50 0 31 Dec 2021
Being Patient and Persistent: Optimizing An Early Stopping Strategy for Deep Learning in Profiled Attacks Servio Paguada L. Batina I. Buhan I. Armendariz AAML 9 6 0 29 Nov 2021
Discovering and Explaining the Representation Bottleneck of DNNs Huiqi Deng Qihan Ren Hao Zhang Quanshi Zhang 39 59 0 11 Nov 2021
Visualizing the Emergence of Intermediate Visual Patterns in DNNs Mingjie Li Shaobo Wang Quanshi Zhang 16 11 0 05 Nov 2021
Representation Edit Distance as a Measure of Novelty J. Alspector 25 6 0 04 Nov 2021
InfoGCL: Information-Aware Graph Contrastive Learning Dongkuan Xu Wei Cheng Dongsheng Luo Haifeng Chen Xiang Zhang 33 192 0 28 Oct 2021
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation Jungbeom Lee Jooyoung Choi J. Mok Sungroh Yoon SSeg 218 134 0 13 Oct 2021
Characterizing Learning Dynamics of Deep Neural Networks via Complex Networks Emanuele La Malfa G. Malfa Giuseppe Nicosia Vito Latora 22 10 0 06 Oct 2021
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review Florian Tambon Gabriel Laberge Le An Amin Nikanjam Paulina Stevia Nouwou Mindom Y. Pequignot Foutse Khomh G. Antoniol E. Merlo François Laviolette 25 65 0 26 Jul 2021
Entropic alternatives to initialization Daniele Musso 37 1 0 16 Jul 2021
A Survey on Data Augmentation for Text Classification Markus Bayer M. Kaufhold Christian A. Reuter 36 334 0 07 Jul 2021
Mitigating severe over-parameterization in deep convolutional neural networks through forced feature abstraction and compression with an entropy-based heuristic Nidhi Gowdra R. Sinha Stephen G. MacDonell W. Yan 21 9 0 27 Jun 2021
Does Optimal Source Task Performance Imply Optimal Pre-training for a Target Task? Steven Gutstein Brent Lance Sanjay Shakkottai 27 1 0 21 Jun 2021
Examining and Combating Spurious Features under Distribution Shift Chunting Zhou Xuezhe Ma Paul Michel Graham Neubig OOD 27 66 0 14 Jun 2021
Credit spread approximation and improvement using random forest regression Mathieu Mercadier J. Lardy 15 47 0 04 Jun 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts Gesina Schwalbe Bettina Finzel XAI 26 184 0 15 May 2021
DirectQE: Direct Pretraining for Machine Translation Quality Estimation Qu Cui Shujian Huang Jiahuan Li Xiang Geng Zaixiang Zheng Guoping Huang Jiajun Chen 13 24 0 15 May 2021
Relative stability toward diffeomorphisms indicates performance in deep nets Leonardo Petrini Alessandro Favero Mario Geiger M. Wyart OOD 31 15 0 06 May 2021
InfoNEAT: Information Theory-based NeuroEvolution of Augmenting Topologies for Side-channel Analysis R. Acharya F. Ganji Domenic Forte AAML 38 24 0 30 Apr 2021
DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning Yuting Gao Jia-Xin Zhuang Xiaowei Guo Hao Cheng Xing Sun Ke Li Feiyue Huang 33 40 0 19 Apr 2021
Reframing Neural Networks: Deep Structure in Overcomplete Representations Calvin Murdock George Cazenavette Simon Lucey BDL 38 4 0 10 Mar 2021
Estimating informativeness of samples with Smooth Unique Information Hrayr Harutyunyan Alessandro Achille Giovanni Paolini Orchid Majumder Avinash Ravichandran Rahul Bhotika Stefano Soatto 19 24 0 17 Jan 2021
Progressive Interpretation Synthesis: Interpreting Task Solving by Quantifying Previously Used and Unused Information Zhengqi He Taro Toyoizumi 15 1 0 08 Jan 2021