Emergence of Invariance and Disentanglement in Deep Representations

5 June 2017

Papers citing "Emergence of Invariance and Disentanglement in Deep Representations"

43 / 93 papers shown

Title
Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting Zeke Xie Fengxiang He Shaopeng Fu Issei Sato Dacheng Tao Masashi Sugiyama 21 59 0 12 Nov 2020
Usable Information and Evolution of Optimal Representations During Training Michael Kleinman Alessandro Achille Daksh Idnani J. Kao 24 13 0 06 Oct 2020
Domain-invariant Similarity Activation Map Contrastive Learning for Retrieval-based Long-term Visual Localization Hanjiang Hu Hesheng Wang Zhe Liu Weidong Chen 27 27 0 16 Sep 2020
DualDE: Dually Distilling Knowledge Graph Embedding for Faster and Cheaper Reasoning Yushan Zhu Wen Zhang Mingyang Chen Hui Chen Xu-Xin Cheng Wei Zhang Huajun Chen Zhejiang University 14 27 0 13 Sep 2020
When is invariance useful in an Out-of-Distribution Generalization problem ? Masanori Koyama Shoichiro Yamaguchi OOD 31 65 0 04 Aug 2020
$Beyond $\mathcal{H}$-Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence$ Beyond $\mathcal{H}$ -Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence Changjian Shui Qi Chen Jun Wen Fan Zhou Christian Gagné Boyu Wang 38 22 0 30 Jul 2020
Adversarial Training Reduces Information and Improves Transferability M. Terzi Alessandro Achille Marco Maggipinto Gian Antonio Susto AAML 19 23 0 22 Jul 2020
Interpreting and Disentangling Feature Components of Various Complexity from DNNs Jie Ren Mingjie Li Zexu Liu Quanshi Zhang CoGe 11 18 0 29 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 21 3 0 10 Jun 2020
Generalization Bounds via Information Density and Conditional Information Density Fredrik Hellström G. Durisi 27 65 0 16 May 2020
Adversarial Latent Autoencoders Stanislav Pidhorskyi Donald Adjeroh Gianfranco Doretto GAN DRL 40 259 0 09 Apr 2020
Guided Variational Autoencoder for Disentanglement Learning Zheng Ding Yifan Xu Weijian Xu Gaurav Parmar Yang Yang Max Welling Z. Tu DRL CoGe 23 106 0 02 Apr 2020
Unpacking Information Bottlenecks: Unifying Information-Theoretic Objectives in Deep Learning Andreas Kirsch Clare Lyle Y. Gal 19 16 0 27 Mar 2020
On Information Plane Analyses of Neural Network Classifiers -- A Review Bernhard C. Geiger 26 50 0 21 Mar 2020
The Variational InfoMax Learning Objective Vincenzo Crescimanna Bruce P. Graham 11 0 0 07 Mar 2020
Semi-Supervised StyleGAN for Disentanglement Learning Weili Nie Tero Karras Animesh Garg Shoubhik Debhath Anjul Patney Ankit B. Patel Anima Anandkumar DRL 89 72 0 06 Mar 2020
NestedVAE: Isolating Common Factors via Weak Supervision M. Vowels Necati Cihan Camgöz Richard Bowden CML DRL 26 21 0 26 Feb 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 24 639 0 20 Feb 2020
CEB Improves Model Robustness Ian S. Fischer Alexander A. Alemi AAML 19 28 0 13 Feb 2020
Unsupervised Representation Disentanglement using Cross Domain Features and Adversarial Learning in Variational Autoencoder based Voice Conversion Wen-Chin Huang Hao Luo Hsin-Te Hwang Chen-Chou Lo Yu-Huai Peng Yu Tsao Hsin-Min Wang DRL 9 42 0 22 Jan 2020
Learning credit assignment Chan Li Haiping Huang 10 7 0 10 Jan 2020
Information in Infinite Ensembles of Infinitely-Wide Neural Networks Ravid Shwartz-Ziv Alexander A. Alemi 19 21 0 20 Nov 2019
Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations Jan Stühmer Richard Turner Sebastian Nowozin DRL BDL CoGe 111 25 0 05 Sep 2019
Hangul Fonts Dataset: a Hierarchical and Compositional Dataset for Investigating Learned Representations J. Livezey Ahyeon Hwang Jacob Yeung K. Bouchard 28 0 0 23 May 2019
Minimal Achievable Sufficient Statistic Learning Milan Cvitkovic Günther Koliander 17 12 0 19 May 2019
Task2Vec: Task Embedding for Meta-Learning Alessandro Achille Michael Lam Rahul Tewari Avinash Ravichandran Subhransu Maji Charless C. Fowlkes Stefano Soatto Pietro Perona SSL 17 309 0 10 Feb 2019
Excessive Invariance Causes Adversarial Vulnerability J. Jacobsen Jens Behrmann R. Zemel Matthias Bethge AAML 20 166 0 01 Nov 2018
Analyzing biological and artificial neural networks: challenges with opportunities for synergy? David Barrett Ari S. Morcos Jakob H. Macke AI4CE 13 110 0 31 Oct 2018
Interpretable Neuron Structuring with Graph Spectral Regularization Alexander Tong David van Dijk Jay S. Stanley Matthew Amodio Kristina M. Yim R. Muhle J. Noonan Guy Wolf Smita Krishnaswamy 19 6 0 30 Sep 2018
Distributed Variational Representation Learning Iñaki Estella Aguerri A. Zaidi 15 71 0 11 Jul 2018
Deformable Generator Networks: Unsupervised Disentanglement of Appearance and Geometry X. Xing Ruiqi Gao Tian Han Song-Chun Zhu Ying Nian Wu DRL 19 28 0 16 Jun 2018
Stochastic Gradient/Mirror Descent: Minimax Optimality and Implicit Regularization Navid Azizan B. Hassibi 16 61 0 04 Jun 2018
Mad Max: Affine Spline Insights into Deep Learning Randall Balestriero Richard Baraniuk AI4CE 31 78 0 17 May 2018
SHADE: Information Based Regularization for Deep Learning Michael Blot Thomas Robert Nicolas Thome Matthieu Cord 26 12 0 29 Apr 2018
Factorised spatial representation learning: application in semi-supervised myocardial segmentation A. Chartsias T. Joyce G. Papanastasiou S. Semple M. Williams D. Newby R. Dharmakumar Sotirios A. Tsaftaris DRL 51 69 0 19 Mar 2018
Learning Representations for Neural Network-Based Classification Using the Information Bottleneck Principle Rana Ali Amjad Bernhard C. Geiger 32 195 0 27 Feb 2018
A Walk with SGD Chen Xing Devansh Arpit Christos Tsirigotis Yoshua Bengio 19 118 0 24 Feb 2018
i-RevNet: Deep Invertible Networks J. Jacobsen A. Smeulders Edouard Oyallon 30 331 0 20 Feb 2018
The Role of Information Complexity and Randomization in Representation Learning Matías Vera Pablo Piantanida L. Rey Vega 37 14 0 14 Feb 2018
MINE: Mutual Information Neural Estimation Mohamed Ishmael Belghazi A. Baratin Sai Rajeswar Sherjil Ozair Yoshua Bengio Aaron Courville R. Devon Hjelm DRL 18 1,248 0 12 Jan 2018
A3T: Adversarially Augmented Adversarial Training Akram Erraqabi A. Baratin Yoshua Bengio Simon Lacoste-Julien AAML 30 9 0 12 Jan 2018
Fixing a Broken ELBO Alexander A. Alemi Ben Poole Ian S. Fischer Joshua V. Dillon Rif A. Saurous Kevin Patrick Murphy DRL BDL 36 80 0 01 Nov 2017