Title
Safety and Robustness in Decision Making: Deep Bayesian Recurrent Neural Networks for Somatic Variant Calling in Cancer Geoffroy Dubourg-Felonneau Omar A. Darwish C. Parsons D. Rebergen J. Cassidy Nirmesh Patel Harry W. Clifford OffRL 49 1 0 04 Dec 2019
Deep Probabilistic Models to Detect Data Poisoning Attacks Mahesh Subedar Nilesh A. Ahuja R. Krishnan I. Ndiour Omesh Tickoo AAML TDI 112 26 0 03 Dec 2019
A Novel Unsupervised Post-Processing Calibration Method for DNNS with Robustness to Domain Shift A. Mozafari H. Gomes Christian Gagné 89 0 0 25 Nov 2019
Parameters Estimation for the Cosmic Microwave Background with Bayesian Neural Networks Héctor J. Hortúa Riccardo Volpi D. Marinelli Luigi Malagò BDL 217 25 0 19 Nov 2019
A Modular Deep Learning Pipeline for Galaxy-Scale Strong Gravitational Lens Detection and Modeling Sandeep Madireddy Nesar Ramachandra Nan Li James P. Butler Dali Wang Salman Habib K. Heitmann The LSST Dark Energy Science Collaboration 200 5 0 10 Nov 2019
Generative Well-intentioned NetworksNeural Information Processing Systems (NeurIPS), 2019 J. Cosentino Jun Zhu AI4CE 66 2 0 28 Oct 2019
We Know Where We Don't Know: 3D Bayesian CNNs for Credible Geometric Uncertainty T. LaBonte Carianne Martinez S. Roberts UQCV 3DV 129 33 0 23 Oct 2019
Scaling up Psychology via Scientific Regret Minimization: A Case Study in Moral Decisions Mayank Agrawal Joshua C. Peterson Thomas Griffiths 102 2 0 16 Oct 2019
Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field ApproximationInternational Conference on Machine Learning (ICML), 2019 Konstantinos Pitas 170 8 0 06 Sep 2019
Variational Federated Multi-Task Learning Luca Corinzia Ami Beuret J. M. Buhmann FedML 222 175 0 14 Jun 2019
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical BayesAAAI Conference on Artificial Intelligence (AAAI), 2019 R. Krishnan Mahesh Subedar Omesh Tickoo BDL 249 58 0 12 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset ShiftNeural Information Processing Systems (NeurIPS), 2019 Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 1.1K 1,908 0 06 Jun 2019
Reliable training and estimation of variance networksNeural Information Processing Systems (NeurIPS), 2019 N. Detlefsen Martin Jørgensen Søren Hauberg UQCV 258 96 0 04 Jun 2019
Learning Sparse Networks Using Targeted Dropout Aidan Gomez Ivan Zhang Siddhartha Rao Kamalakara Divyam Madaan Kevin Swersky Y. Gal Geoffrey E. Hinton 339 99 0 31 May 2019
Functional Variational Bayesian Neural Networks Shengyang Sun Guodong Zhang Jiaxin Shi Roger C. Grosse BDL 255 257 0 14 Mar 2019
Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions M. Mackay Paul Vicol Jonathan Lorraine David Duvenaud Roger C. Grosse 190 179 0 07 Mar 2019
An Empirical Study of Large-Batch Stochastic Gradient Descent with Structured Covariance Noise Yeming Wen Kevin Luk Maxime Gazeau Guodong Zhang Harris Chan Jimmy Ba ODL 317 24 0 21 Feb 2019
Bayesian Layers: A Module for Neural Network Uncertainty Dustin Tran Michael W. Dusenberry Mark van der Wilk Danijar Hafner UQCV BDL 310 134 0 10 Dec 2018
The Relevance of Bayesian Layer Positioning to Model Uncertainty in Deep Bayesian Active Learning Jiaming Zeng Adam Lesnikowski J. Álvarez OOD UQCV BDL 165 31 0 29 Nov 2018
Uncertainty aware audiovisual activity recognition using deep Bayesian variational inference Mahesh Subedar R. Krishnan P. López-Meyer Omesh Tickoo Jonathan Huang BDL EDL UQCV 169 0 0 27 Nov 2018
BAR: Bayesian Activity Recognition using variational inference R. Krishnan Mahesh Subedar S. Bhatnagar BDL UQCV 256 22 0 08 Nov 2018
Simple, Distributed, and Accelerated Probabilistic Programming Like Hui Matthew Hoffman Siyuan Ma Christopher Suter Srinivas Vasudevan Alexey Radul M. Belkin Rif A. Saurous BDL 156 59 0 05 Nov 2018
Closed Form Variational Objectives For Bayesian Neural Networks with a Single Hidden Layer M. Jankowiak BDL 164 2 0 02 Nov 2018
Noise Contrastive Priors for Functional Uncertainty Danijar Hafner Dustin Tran Timothy Lillicrap A. Irpan James Davidson AAML BDL UQCV 285 77 0 24 Jul 2018

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Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches

International Conference on Learning Representations (ICLR), 2018

12 March 2018

Yeming Wen

Paul Vicol

Jimmy Ba

Papers citing "Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches"

24 / 174 papers shown

Title
Safety and Robustness in Decision Making: Deep Bayesian Recurrent Neural Networks for Somatic Variant Calling in Cancer Geoffroy Dubourg-Felonneau Omar A. Darwish C. Parsons D. Rebergen J. Cassidy Nirmesh Patel Harry W. Clifford OffRL 49 1 0 04 Dec 2019
Deep Probabilistic Models to Detect Data Poisoning Attacks Mahesh Subedar Nilesh A. Ahuja R. Krishnan I. Ndiour Omesh Tickoo AAML TDI 112 26 0 03 Dec 2019
A Novel Unsupervised Post-Processing Calibration Method for DNNS with Robustness to Domain Shift A. Mozafari H. Gomes Christian Gagné 89 0 0 25 Nov 2019
Parameters Estimation for the Cosmic Microwave Background with Bayesian Neural Networks Héctor J. Hortúa Riccardo Volpi D. Marinelli Luigi Malagò BDL 217 25 0 19 Nov 2019
A Modular Deep Learning Pipeline for Galaxy-Scale Strong Gravitational Lens Detection and Modeling Sandeep Madireddy Nesar Ramachandra Nan Li James P. Butler Dali Wang Salman Habib K. Heitmann The LSST Dark Energy Science Collaboration 200 5 0 10 Nov 2019
Generative Well-intentioned NetworksNeural Information Processing Systems (NeurIPS), 2019 J. Cosentino Jun Zhu AI4CE 66 2 0 28 Oct 2019
We Know Where We Don't Know: 3D Bayesian CNNs for Credible Geometric Uncertainty T. LaBonte Carianne Martinez S. Roberts UQCV 3DV 129 33 0 23 Oct 2019
Scaling up Psychology via Scientific Regret Minimization: A Case Study in Moral Decisions Mayank Agrawal Joshua C. Peterson Thomas Griffiths 102 2 0 16 Oct 2019
Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field ApproximationInternational Conference on Machine Learning (ICML), 2019 Konstantinos Pitas 170 8 0 06 Sep 2019
Variational Federated Multi-Task Learning Luca Corinzia Ami Beuret J. M. Buhmann FedML 222 175 0 14 Jun 2019
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical BayesAAAI Conference on Artificial Intelligence (AAAI), 2019 R. Krishnan Mahesh Subedar Omesh Tickoo BDL 249 58 0 12 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset ShiftNeural Information Processing Systems (NeurIPS), 2019 Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 1.1K 1,908 0 06 Jun 2019
Reliable training and estimation of variance networksNeural Information Processing Systems (NeurIPS), 2019 N. Detlefsen Martin Jørgensen Søren Hauberg UQCV 258 96 0 04 Jun 2019
Learning Sparse Networks Using Targeted Dropout Aidan Gomez Ivan Zhang Siddhartha Rao Kamalakara Divyam Madaan Kevin Swersky Y. Gal Geoffrey E. Hinton 339 99 0 31 May 2019
Functional Variational Bayesian Neural Networks Shengyang Sun Guodong Zhang Jiaxin Shi Roger C. Grosse BDL 255 257 0 14 Mar 2019
Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions M. Mackay Paul Vicol Jonathan Lorraine David Duvenaud Roger C. Grosse 190 179 0 07 Mar 2019
An Empirical Study of Large-Batch Stochastic Gradient Descent with Structured Covariance Noise Yeming Wen Kevin Luk Maxime Gazeau Guodong Zhang Harris Chan Jimmy Ba ODL 317 24 0 21 Feb 2019
Bayesian Layers: A Module for Neural Network Uncertainty Dustin Tran Michael W. Dusenberry Mark van der Wilk Danijar Hafner UQCV BDL 310 134 0 10 Dec 2018
The Relevance of Bayesian Layer Positioning to Model Uncertainty in Deep Bayesian Active Learning Jiaming Zeng Adam Lesnikowski J. Álvarez OOD UQCV BDL 165 31 0 29 Nov 2018
Uncertainty aware audiovisual activity recognition using deep Bayesian variational inference Mahesh Subedar R. Krishnan P. López-Meyer Omesh Tickoo Jonathan Huang BDL EDL UQCV 169 0 0 27 Nov 2018
BAR: Bayesian Activity Recognition using variational inference R. Krishnan Mahesh Subedar S. Bhatnagar BDL UQCV 256 22 0 08 Nov 2018
Simple, Distributed, and Accelerated Probabilistic Programming Like Hui Matthew Hoffman Siyuan Ma Christopher Suter Srinivas Vasudevan Alexey Radul M. Belkin Rif A. Saurous BDL 156 59 0 05 Nov 2018
Closed Form Variational Objectives For Bayesian Neural Networks with a Single Hidden Layer M. Jankowiak BDL 164 2 0 02 Nov 2018
Noise Contrastive Priors for Functional Uncertainty Danijar Hafner Dustin Tran Timothy Lillicrap A. Irpan James Davidson AAML BDL UQCV 285 77 0 24 Jul 2018

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