Multiplicative Normalizing Flows for Variational Bayesian Neural Networks

6 March 2017

Papers citing "Multiplicative Normalizing Flows for Variational Bayesian Neural Networks"

50 / 114 papers shown

Title
Neural Bootstrapper Minsuk Shin Hyungjoon Cho Hyun-Seok Min Sungbin Lim UQCV BDL 22 7 0 02 Oct 2020
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference Bang An Jie Lyu Zhenyi Wang Chunyuan Li Changwei Hu Fei Tan Ruiyi Zhang Yifan Hu Changyou Chen AAML 22 28 0 20 Sep 2020
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems Zhe Chen Yuyan Wang Dong Lin D. Cheng Lichan Hong Ed H. Chi Claire Cui 28 16 0 17 Aug 2020
Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles Tárik S. Salem H. Langseth H. Ramampiaro UQCV 21 36 0 19 Jul 2020
Variational Inference with Continuously-Indexed Normalizing Flows Anthony L. Caterini R. Cornish Dino Sejdinovic Arnaud Doucet BDL 24 19 0 10 Jul 2020
Quantifying and Leveraging Predictive Uncertainty for Medical Image Assessment Florin-Cristian Ghesu Bogdan Georgescu Awais Mansoor Y. Yoo Eli Gibson ... Ramandeep Singh S. Digumarthy M. Kalra Sasa Grbic Dorin Comaniciu UQCV EDL 23 55 0 08 Jul 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 37 199 0 22 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
$On the Optimal Weighted $\ell_2$ Regularization in Overparameterized Linear Regression$ On the Optimal Weighted $\ell_2$ Regularization in Overparameterized Linear Regression Denny Wu Ji Xu 33 121 0 10 Jun 2020
Uncertainty-Aware Deep Classifiers using Generative Models Murat Sensoy Lance M. Kaplan Federico Cerutti Maryam Saleki UQCV OOD 22 73 0 07 Jun 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
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 33 277 0 24 Feb 2020
Being Bayesian about Categorical Probability Taejong Joo U. Chung Minji Seo UQCV BDL 25 58 0 19 Feb 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models Chin-Wei Huang Laurent Dinh Aaron Courville DRL 31 87 0 17 Feb 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 57 176 0 16 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
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights Theofanis Karaletsos T. Bui BDL 20 23 0 10 Feb 2020
OoDAnalyzer: Interactive Analysis of Out-of-Distribution Samples Changjian Chen Jun Yuan Yafeng Lu Yang Liu Hang Su Songtao Yuan Shixia Liu OODD 26 63 0 08 Feb 2020
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation Chence Shi Minkai Xu Zhaocheng Zhu Weinan Zhang Ming Zhang Jian Tang 66 426 0 26 Jan 2020
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 62 1,631 0 05 Dec 2019
Deep Ensembles: A Loss Landscape Perspective Stanislav Fort Huiyi Hu Balaji Lakshminarayanan OOD UQCV 29 619 0 05 Dec 2019
Bayesian Graph Convolutional Neural Networks using Node Copying Soumyasundar Pal Florence Regol Mark J. Coates BDL GNN 33 12 0 08 Nov 2019
Adaptative Inference Cost With Convolutional Neural Mixture Models Adria Ruiz Jakob Verbeek VLM 30 22 0 19 Aug 2019
Unsupervised Domain Adaptation via Calibrating Uncertainties Ligong Han Yang Zou Ruijiang Gao Lezi Wang Dimitris N. Metaxas 19 30 0 25 Jul 2019
Quality of Uncertainty Quantification for Bayesian Neural Network Inference Jiayu Yao Weiwei Pan S. Ghosh Finale Doshi-Velez UQCV BDL 32 113 0 24 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
Neural Spline Flows Conor Durkan Artur Bekasov Iain Murray George Papamakarios DRL 29 745 0 10 Jun 2019
Analyzing the Role of Model Uncertainty for Electronic Health Records Michael W. Dusenberry Dustin Tran Edward Choi Jonas Kemp Jeremy Nixon Ghassen Jerfel Katherine A. Heller Andrew M. Dai 18 117 0 10 Jun 2019
DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep Networks Aryan Mobiny H. Nguyen S. Moulik Naveen Garg Carol C. Wu UQCV BDL 20 155 0 07 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 47 1,658 0 06 Jun 2019
Walsh-Hadamard Variational Inference for Bayesian Deep Learning Simone Rossi Sébastien Marmin Maurizio Filippone BDL 32 14 0 27 May 2019
Ensemble Model Patching: A Parameter-Efficient Variational Bayesian Neural Network Oscar Chang Yuling Yao David Williams-King Hod Lipson BDL UQCV 32 8 0 23 May 2019
Functional Variational Bayesian Neural Networks Shengyang Sun Guodong Zhang Jiaxin Shi Roger C. Grosse BDL 22 235 0 14 Mar 2019
Calibration of Encoder Decoder Models for Neural Machine Translation Aviral Kumar Sunita Sarawagi 27 98 0 03 Mar 2019
Hypernetwork functional image representation Sylwester Klocek Lukasz Maziarka Maciej Wołczyk Jacek Tabor Jakub Nowak Marek Śmieja SupR 3DH 24 90 0 27 Feb 2019
Emerging Convolutions for Generative Normalizing Flows Emiel Hoogeboom Rianne van den Berg Max Welling DRL 24 98 0 30 Jan 2019
Knowing what you know in brain segmentation using Bayesian deep neural networks Patrick McClure Nao Rho J. Lee Jakub R. Kaczmarzyk C. Zheng Satrajit S. Ghosh D. Nielson Adam G. Thomas P. Bandettini Francisco Pereira UQCV 3DV BDL 24 52 0 03 Dec 2018
Bayesian graph convolutional neural networks for semi-supervised classification Yingxue Zhang Soumyasundar Pal Mark J. Coates Deniz Üstebay GNN BDL 21 227 0 27 Nov 2018
Agent Embeddings: A Latent Representation for Pole-Balancing Networks Oscar Chang Robert Kwiatkowski Siyuan Chen Hod Lipson 27 6 0 12 Nov 2018
Good Initializations of Variational Bayes for Deep Models Simone Rossi Pietro Michiardi Maurizio Filippone BDL 17 21 0 18 Oct 2018
Deterministic Variational Inference for Robust Bayesian Neural Networks Anqi Wu Sebastian Nowozin Edward Meeds Richard Turner José Miguel Hernández-Lobato Alexander L. Gaunt UQCV AAML BDL 29 16 0 09 Oct 2018
Probabilistic Meta-Representations Of Neural Networks Theofanis Karaletsos Peter Dayan Zoubin Ghahramani BDL 12 27 0 01 Oct 2018
Boosting Trust Region Policy Optimization by Normalizing Flows Policy Yunhao Tang Shipra Agrawal TPM 30 29 0 27 Sep 2018
Neural Processes M. Garnelo Jonathan Richard Schwarz Dan Rosenbaum Fabio Viola Danilo Jimenez Rezende S. M. Ali Eslami Yee Whye Teh BDL UQCV GP 19 506 0 04 Jul 2018
Leveraging Uncertainty Estimates for Predicting Segmentation Quality Terrance Devries Graham W. Taylor UQCV 25 114 0 02 Jul 2018
Uncertainty in Multitask Transfer Learning Alexandre Lacoste Boris N. Oreshkin Wonchang Chung Thomas Boquet Negar Rostamzadeh David M. Krueger BDL UQCV SSL 24 21 0 20 Jun 2018
Meta-Learning for Stochastic Gradient MCMC Wenbo Gong Yingzhen Li José Miguel Hernández-Lobato BDL 38 44 0 12 Jun 2018
Evidential Deep Learning to Quantify Classification Uncertainty Murat Sensoy Lance M. Kaplan M. Kandemir OOD UQCV EDL BDL 90 953 0 05 Jun 2018