Weight Uncertainty in Neural Networks

20 May 2015

Papers citing "Weight Uncertainty in Neural Networks"

50 / 396 papers shown

Title
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts Bertrand Charpentier Daniel Zügner Stephan Günnemann UQCV UD EDL BDL 29 169 0 16 Jun 2020
Deep Autoencoding Topic Model with Scalable Hybrid Bayesian Inference Hao Zhang Bo Chen Yulai Cong D. Guo Hongwei Liu Mingyuan Zhou BDL 27 27 0 15 Jun 2020
Depth Uncertainty in Neural Networks Javier Antorán J. Allingham José Miguel Hernández-Lobato UQCV OOD BDL 43 100 0 15 Jun 2020
Detecting unusual input to neural networks Jörg Martin Clemens Elster AAML 17 7 0 15 Jun 2020
A benchmark study on reliable molecular supervised learning via Bayesian learning Doyeong Hwang Grace Lee Hanseok Jo Seyoul Yoon Seongok Ryu 32 9 0 12 Jun 2020
Uncertainty-Aware Deep Classifiers using Generative Models Murat Sensoy Lance M. Kaplan Federico Cerutti Maryam Saleki UQCV OOD 25 73 0 07 Jun 2020
An Empirical Analysis of the Impact of Data Augmentation on Knowledge Distillation Deepan Das Haley Massa Abhimanyu Kulkarni Theodoros Rekatsinas 29 18 0 06 Jun 2020
Bayesian Neural Networks at Scale: A Performance Analysis and Pruning Study Himanshu Sharma Elise Jennings BDL 27 3 0 23 May 2020
Efficient Ensemble Model Generation for Uncertainty Estimation with Bayesian Approximation in Segmentation Hong Joo Lee S. T. Kim Hakmin Lee Nassir Navab Yong Man Ro UQCV 16 7 0 21 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
On the uncertainty of self-supervised monocular depth estimation Matteo Poggi Filippo Aleotti Fabio Tosi S. Mattoccia UQCV MDE 33 263 0 13 May 2020
Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models Jayaraman J. Thiagarajan Bindya Venkatesh Rushil Anirudh P. Bremer J. Gaffney G. Anderson B. Spears 18 21 0 05 May 2020
Probabilistic Safety for Bayesian Neural Networks Matthew Wicker Luca Laurenti A. Patané Marta Z. Kwiatkowska AAML 14 52 0 21 Apr 2020
Estimating Uncertainty and Interpretability in Deep Learning for Coronavirus (COVID-19) Detection Biraja Ghoshal A. Tucker UQCV OOD 24 378 0 22 Mar 2020
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning Jize Zhang B. Kailkhura T. Y. Han UQCV 30 219 0 16 Mar 2020
A Simple Probabilistic Method for Deep Classification under Input-Dependent Label Noise Mark Collier Basil Mustafa Efi Kokiopoulou Rodolphe Jenatton Jesse Berent UQCV NoLa 41 0 0 15 Mar 2020
Individual Claims Forecasting with Bayesian Mixture Density Networks Kevin Kuo AI4TS 27 13 0 05 Mar 2020
Uncertainty Estimation Using a Single Deep Deterministic Neural Network Joost R. van Amersfoort Lewis Smith Yee Whye Teh Y. Gal UQCV BDL 14 55 0 04 Mar 2020
Fast Predictive Uncertainty for Classification with Bayesian Deep Networks Marius Hobbhahn Agustinus Kristiadi Philipp Hennig BDL UQCV 78 32 0 02 Mar 2020
AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC Ruqi Zhang A. Feder Cooper Christopher De Sa 10 18 0 29 Feb 2020
Reinforcement Learning through Active Inference Alexander Tschantz Beren Millidge A. Seth Christopher L. Buckley AI4CE 31 69 0 28 Feb 2020
Uncertainty Quantification for Sparse Deep Learning Yuexi Wang Veronika Rockova BDL UQCV 36 31 0 26 Feb 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 35 277 0 24 Feb 2020
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation Dmitry Molchanov Alexander Lyzhov Yuliya Molchanova Arsenii Ashukha Dmitry Vetrov TPM 27 84 0 21 Feb 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 24 641 0 20 Feb 2020
Being Bayesian about Categorical Probability Taejong Joo U. Chung Minji Seo UQCV BDL 27 58 0 19 Feb 2020
Gravitational-wave parameter estimation with autoregressive neural network flows Stephen R. Green C. Simpson J. Gair BDL 83 87 0 18 Feb 2020
A Financial Service Chatbot based on Deep Bidirectional Transformers S. Yu Yuxin Chen Hussain Zaidi 30 33 0 17 Feb 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning Arsenii Ashukha Alexander Lyzhov Dmitry Molchanov Dmitry Vetrov UQCV FedML 35 314 0 15 Feb 2020
Estimating Uncertainty Intervals from Collaborating Networks Tianhui Zhou Yitong Li Yuan Wu David Carlson UQCV 30 16 0 12 Feb 2020
Robustness of Bayesian Neural Networks to Gradient-Based Attacks Ginevra Carbone Matthew Wicker Luca Laurenti A. Patané Luca Bortolussi G. Sanguinetti AAML 38 77 0 11 Feb 2020
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights Theofanis Karaletsos T. Bui BDL 20 23 0 10 Feb 2020
Safety Concerns and Mitigation Approaches Regarding the Use of Deep Learning in Safety-Critical Perception Tasks Oliver Willers Sebastian Sudholt Shervin Raafatnia Stephanie Abrecht 28 80 0 22 Jan 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
Making Sense of Reinforcement Learning and Probabilistic Inference Brendan O'Donoghue Ian Osband Catalin Ionescu OffRL 27 48 0 03 Jan 2020
Uncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning Andreas Sedlmeier Thomas Gabor Thomy Phan Lenz Belzner Claudia Linnhoff-Popien 21 25 0 31 Dec 2019
TRADI: Tracking deep neural network weight distributions for uncertainty estimation Gianni Franchi Andrei Bursuc Emanuel Aldea Séverine Dubuisson Isabelle Bloch UQCV 26 51 0 24 Dec 2019
Parting with Illusions about Deep Active Learning Sudhanshu Mittal Maxim Tatarchenko Özgün Çiçek Thomas Brox VLM 27 59 0 11 Dec 2019
Deep Ensembles: A Loss Landscape Perspective Stanislav Fort Huiyi Hu Balaji Lakshminarayanan OOD UQCV 38 620 0 05 Dec 2019
Distance-Based Learning from Errors for Confidence Calibration Chen Xing Sercan Ö. Arik Zizhao Zhang Tomas Pfister FedML 23 39 0 03 Dec 2019
Learning Rate Dropout Huangxing Lin Weihong Zeng Xinghao Ding Yue Huang Yihong Zhuang John Paisley ODL 18 9 0 30 Nov 2019
Scaling active inference Alexander Tschantz Manuel Baltieri A. Seth Christopher L. Buckley BDL AI4CE 19 68 0 24 Nov 2019
Multivariate Uncertainty in Deep Learning Rebecca L. Russell Christopher P. Reale BDL UQCV 17 68 0 31 Oct 2019
Thompson Sampling via Local Uncertainty Zhendong Wang Mingyuan Zhou 16 19 0 30 Oct 2019
Learning an Uncertainty-Aware Object Detector for Autonomous Driving Gregory P. Meyer Niranjan Thakurdesai UQCV 25 60 0 24 Oct 2019
Continual Learning Using Bayesian Neural Networks Honglin Li Payam Barnaghi Shirin Enshaeifar F. Ganz BDL 19 38 0 09 Oct 2019
On the Limits of Learning to Actively Learn Semantic Representations Omri Koshorek Gabriel Stanovsky Yichu Zhou Vivek Srikumar Jonathan Berant OffRL 27 9 0 05 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 25 7 0 01 Oct 2019
Addressing Failure Prediction by Learning Model Confidence Charles Corbière Nicolas Thome Avner Bar-Hen Matthieu Cord P. Pérez 33 283 0 01 Oct 2019
Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving Control Rhiannon Michelmore Matthew Wicker Luca Laurenti L. Cardelli Y. Gal Marta Z. Kwiatkowska BDL 18 105 0 21 Sep 2019