Variational Dropout and the Local Reparameterization Trick

8 June 2015

Papers citing "Variational Dropout and the Local Reparameterization Trick"

50 / 286 papers shown

Title
Operation-Aware Soft Channel Pruning using Differentiable Masks Minsoo Kang Bohyung Han AAML 35 138 0 08 Jul 2020
Improving Calibration through the Relationship with Adversarial Robustness Yao Qin Xuezhi Wang Alex Beutel Ed H. Chi AAML 40 25 0 29 Jun 2020
Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions Ahmed Alaa M. Schaar UD UQCV BDL TDI 21 53 0 29 Jun 2020
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift Alex J. Chan Ahmed Alaa Zhaozhi Qian M. Schaar UQCV BDL OOD 28 38 0 26 Jun 2020
Bayesian Neural Networks: An Introduction and Survey Ethan Goan Clinton Fookes BDL UQCV 35 199 0 22 Jun 2020
Gradient-EM Bayesian Meta-learning Yayi Zou Xiaoqi Lu BDL 33 16 0 21 Jun 2020
Estimating Model Uncertainty of Neural Networks in Sparse Information Form Jongseo Lee Matthias Humt Jianxiang Feng Rudolph Triebel BDL UQCV 38 46 0 20 Jun 2020
Calibration of Model Uncertainty for Dropout Variational Inference M. Laves Sontje Ihler Karl-Philipp Kortmann T. Ortmaier BDL UQCV 32 18 0 20 Jun 2020
Towards Adaptive Benthic Habitat Mapping J. Shields Oscar Pizarro Stefan B. Williams 16 14 0 20 Jun 2020
How Much Can I Trust You? -- Quantifying Uncertainties in Explaining Neural Networks Kirill Bykov Marina M.-C. Höhne Klaus-Robert Muller Shinichi Nakajima Marius Kloft UQCV FAtt 27 31 0 16 Jun 2020
Depth Uncertainty in Neural Networks Javier Antorán J. Allingham José Miguel Hernández-Lobato UQCV OOD BDL 41 100 0 15 Jun 2020
Detecting unusual input to neural networks Jörg Martin Clemens Elster AAML 17 7 0 15 Jun 2020
PatchUp: A Feature-Space Block-Level Regularization Technique for Convolutional Neural Networks Mojtaba Faramarzi Mohammad Amini Akilesh Badrinaaraayanan Vikas Verma A. Chandar AAML 34 31 0 14 Jun 2020
Uncertainty-Aware Deep Classifiers using Generative Models Murat Sensoy Lance M. Kaplan Federico Cerutti Maryam Saleki UQCV OOD 20 73 0 07 Jun 2020
An Overview of Neural Network Compression James OÑeill AI4CE 45 98 0 05 Jun 2020
UFO-BLO: Unbiased First-Order Bilevel Optimization Valerii Likhosherstov Xingyou Song K. Choromanski Jared Davis Adrian Weller 32 7 0 05 Jun 2020
Gradient Monitored Reinforcement Learning Mohammed Sharafath Abdul Hameed Gavneet Singh Chadha Andreas Schwung S. Ding 33 10 0 25 May 2020
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes Sebastian W. Ober Laurence Aitchison BDL 26 60 0 17 May 2020
TraDE: Transformers for Density Estimation Rasool Fakoor Pratik Chaudhari Jonas W. Mueller Alex Smola 20 30 0 06 Apr 2020
On Calibration of Mixup Training for Deep Neural Networks Juan Maroñas D. Ramos-Castro Roberto Paredes Palacios UQCV 30 6 0 22 Mar 2020
The Variational InfoMax Learning Objective Vincenzo Crescimanna Bruce P. Graham 16 0 0 07 Mar 2020
Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks Yehui Tang Yunhe Wang Yixing Xu Boxin Shi Chao Xu Chunjing Xu Chang Xu 17 38 0 23 Feb 2020
Being Bayesian about Categorical Probability Taejong Joo U. Chung Minji Seo UQCV BDL 25 58 0 19 Feb 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning Arsenii Ashukha Alexander Lyzhov Dmitry Molchanov Dmitry Vetrov UQCV FedML 33 314 0 15 Feb 2020
Graph Convolutional Gaussian Processes For Link Prediction Felix L. Opolka Pietro Lio GNN 27 15 0 11 Feb 2020
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights Theofanis Karaletsos T. Bui BDL 20 23 0 10 Feb 2020
Resource-Efficient Neural Networks for Embedded Systems Wolfgang Roth Günther Schindler Lukas Pfeifenberger Robert Peharz Sebastian Tschiatschek Holger Fröning Franz Pernkopf Zoubin Ghahramani 34 47 0 07 Jan 2020
Improving Polyphonic Music Models with Feature-Rich Encoding Omar Peracha 32 12 0 26 Nov 2019
IPOD: An Industrial and Professional Occupations Dataset and its Applications to Occupational Data Mining and Analysis Junhua Liu Yung Chuen Ng Kristin L. Wood Kwan Hui Lim 22 6 0 22 Oct 2019
Kernelized Wasserstein Natural Gradient Michael Arbel Arthur Gretton Wuchen Li Guido Montúfar 18 22 0 21 Oct 2019
Natural Question Generation with Reinforcement Learning Based Graph-to-Sequence Model Yu Chen Lingfei Wu Mohammed J Zaki 19 11 0 19 Oct 2019
Action Anticipation for Collaborative Environments: The Impact of Contextual Information and Uncertainty-Based Prediction Clebeson Canuto dos Santos Plinio Moreno J. L. A. Samatelo R. Vassallo J. Santos-Victor 22 7 0 01 Oct 2019
Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models Cheolhyoung Lee Kyunghyun Cho Wanmo Kang MoE 249 205 0 25 Sep 2019
Image Captioning with Sparse Recurrent Neural Network J. Tan Chee Seng Chan Joon Huang Chuah VLM 29 6 0 28 Aug 2019
Marginally-calibrated deep distributional regression Nadja Klein David J. Nott M. Smith UQCV 32 14 0 26 Aug 2019
A Kings Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation Amir Atapour-Abarghouei Stephen Bonner A. Mcgough 29 7 0 19 Aug 2019
Adaptative Inference Cost With Convolutional Neural Mixture Models Adria Ruiz Jakob Verbeek VLM 30 22 0 19 Aug 2019
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems Anna Kuzina Evgenii Egorov Evgeny Burnaev MedIm 29 19 0 15 Aug 2019
Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation Yu Chen Lingfei Wu Mohammed J Zaki GNN 17 153 0 14 Aug 2019
DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks Simon Wiedemann H. Kirchhoffer Stefan Matlage Paul Haase Arturo Marbán ... Ahmed Osman D. Marpe H. Schwarz Thomas Wiegand Wojciech Samek 49 92 0 27 Jul 2019
Adaptive Regularization via Residual Smoothing in Deep Learning Optimization Jung-Kyun Cho Junseok Kwon Byung-Woo Hong 31 1 0 23 Jul 2019
Subspace Inference for Bayesian Deep Learning Pavel Izmailov Wesley J. Maddox Polina Kirichenko T. Garipov Dmitry Vetrov A. Wilson UQCV BDL 38 142 0 17 Jul 2019
Supervised Uncertainty Quantification for Segmentation with Multiple Annotations Shi Hu Daniel E. Worrall Stefan Knegt Bastiaan S. Veeling Henkjan Huisman Max Welling UQCV 16 94 0 03 Jul 2019
Deep Active Learning with Adaptive Acquisition Manuel Haussmann Fred Hamprecht M. Kandemir 22 41 0 27 Jun 2019
The Functional Neural Process Christos Louizos Xiahan Shi Klamer Schutte Max Welling BDL 38 77 0 19 Jun 2019
Stochastic Neural Network with Kronecker Flow Chin-Wei Huang Ahmed Touati Pascal Vincent Gintare Karolina Dziugaite Alexandre Lacoste Aaron Courville BDL 27 8 0 10 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 29 1,658 0 06 Jun 2019
Practical Deep Learning with Bayesian Principles Kazuki Osawa S. Swaroop Anirudh Jain Runa Eschenhagen Richard Turner Rio Yokota Mohammad Emtiyaz Khan BDL UQCV 56 240 0 06 Jun 2019
Non-linear Multitask Learning with Deep Gaussian Processes Ayman Boustati Theodoros Damoulas R. Savage BDL 19 5 0 29 May 2019
SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers Igor Fedorov Ryan P. Adams Matthew Mattina P. Whatmough 13 164 0 28 May 2019