Multiplicative Normalizing Flows for Variational Bayesian Neural Networks

6 March 2017

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

50 / 102 papers shown

Title
Comparing Uncertainty Measurement and Mitigation Methods for Large Language Models: A Systematic Review Toghrul Abbasli Kentaroh Toyoda Yuan Wang Leon Witt Muhammad Asif Ali Yukai Miao Dan Li Qingsong Wei UQCV 92 0 0 25 Apr 2025
Bayesian Computation in Deep Learning Wenlong Chen Bolian Li Ruqi Zhang Yingzhen Li BDL 75 0 0 25 Feb 2025
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models Daniela de Albuquerque John Pearson DiffM 64 0 0 03 Jan 2025
Uncertainty Quantification with Bayesian Higher Order ReLU KANs J. Giroux Cristiano Fanelli UQCV 40 1 0 02 Oct 2024
Unmasking Social Bots: How Confident Are We? J. Giroux Ariyarathne Gangani Alexander C. Nwala C. Fanelli 31 1 0 18 Jul 2024
Improving robustness to corruptions with multiplicative weight perturbations Trung Trinh Markus Heinonen Luigi Acerbi Samuel Kaski 44 0 0 24 Jun 2024
Variational Bayesian Optimal Experimental Design with Normalizing Flows Jiayuan Dong Christian L. Jacobsen Mehdi Khalloufi Maryam Akram Wanjiao Liu Karthik Duraisamy Xun Huan BDL 54 5 0 08 Apr 2024
HyperFast: Instant Classification for Tabular Data David Bonet D. M. Montserrat Xavier Giró-i-Nieto A. Ioannidis 46 15 0 22 Feb 2024
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks Ruigang Wang Krishnamurthy Dvijotham I. Manchester 36 5 0 02 Feb 2024
Uncertainty Visualization via Low-Dimensional Posterior Projections Omer Yair E. Nehme T. Michaeli UQCV 38 2 0 12 Dec 2023
Implicit Variational Inference for High-Dimensional Posteriors Anshuk Uppal Kristoffer Stensbo-Smidt Wouter Boomsma J. Frellsen BDL 26 1 0 10 Oct 2023
Failure Detection for Motion Prediction of Autonomous Driving: An Uncertainty Perspective Wenbo Shao Yan Xu Liang Peng Jun Li Hong Wang 32 15 0 11 Jan 2023
Constraining cosmological parameters from N-body simulations with Variational Bayesian Neural Networks Héctor J. Hortúa L. '. García Leonardo Castañeda C. BDL 24 4 0 09 Jan 2023
Annealing Double-Head: An Architecture for Online Calibration of Deep Neural Networks Erdong Guo D. Draper Maria de Iorio 35 0 0 27 Dec 2022
Bayesian posterior approximation with stochastic ensembles Oleksandr Balabanov Bernhard Mehlig H. Linander BDL UQCV 27 5 0 15 Dec 2022
Copula Conformal Prediction for Multi-step Time Series Forecasting S. Sun Rose Yu AI4TS 29 22 0 06 Dec 2022
What's Behind the Mask: Estimating Uncertainty in Image-to-Image Problems Gilad Kutiel Regev Cohen Michael Elad Daniel Freedman UQCV 27 5 0 28 Nov 2022
ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints Yinpeng Dong Shouwei Ruan Hang Su Cai Kang Xingxing Wei Junyi Zhu AAML 30 49 0 08 Oct 2022
Conformal Methods for Quantifying Uncertainty in Spatiotemporal Data: A Survey S. Sun AI4CE 38 10 0 08 Sep 2022
Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks Daiwei Zhang Tianci Liu Jian Kang BDL UQCV 35 2 0 12 Jun 2022
Quantum-Aided Meta-Learning for Bayesian Binary Neural Networks via Born Machines I. Nikoloska Osvaldo Simeone AI4CE 11 3 0 31 Mar 2022
A Deep Bayesian Neural Network for Cardiac Arrhythmia Classification with Rejection from ECG Recordings Wen-Rang Zhang Xinxin Di Guodong Wei Shijia Geng Zhaoji Fu linda Qiao UQCV BDL 11 2 0 26 Feb 2022
AdaAnn: Adaptive Annealing Scheduler for Probability Density Approximation Emma R. Cobian J. Hauenstein Fang Liu Daniele E. Schiavazzi 19 4 0 01 Feb 2022
GradTail: Learning Long-Tailed Data Using Gradient-based Sample Weighting Zhao Chen Vincent Casser Henrik Kretzschmar Dragomir Anguelov 28 5 0 16 Jan 2022
Generalized Normalizing Flows via Markov Chains Paul Hagemann J. Hertrich Gabriele Steidl BDL DiffM AI4CE 30 22 0 24 Nov 2021
A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel Yindong Chen Yiwei Wang Lulu Kang Chun Liu 23 1 0 21 Nov 2021
Interactive Medical Image Segmentation with Self-Adaptive Confidence Calibration Wenhao Li Qisen Xu Chuyun Shen Bin Hu Fengping Zhu Yuxin Li Bo Jin Xiangfeng Wang 30 5 0 15 Nov 2021
Is MC Dropout Bayesian? Loic Le Folgoc V. Baltatzis S. Desai A. Devaraj S. Ellis O. M. Manzanera A. Nair Huaqi Qiu J. Schnabel Ben Glocker BDL OOD UQCV 30 39 0 08 Oct 2021
Pathologies in priors and inference for Bayesian transformers Tristan Cinquin Alexander Immer Max Horn Vincent Fortuin UQCV BDL MedIm 34 9 0 08 Oct 2021
TyXe: Pyro-based Bayesian neural nets for Pytorch H. Ritter Theofanis Karaletsos OOD MU BDL 28 6 0 01 Oct 2021
Introspective Robot Perception using Smoothed Predictions from Bayesian Neural Networks Jianxiang Feng M. Durner Zoltán-Csaba Márton Ferenc Bálint-Benczédi Rudolph Triebel UQCV BDL 13 11 0 27 Sep 2021
Uncertainty-Aware Reliable Text Classification Yibo Hu Latifur Khan EDL UQCV 33 33 0 15 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 59 1,111 0 07 Jul 2021
Transformation Models for Flexible Posteriors in Variational Bayes Sefan Hörtling Daniel Dold Oliver Durr Beate Sick 16 0 0 01 Jun 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 31 124 0 14 May 2021
A Bit More Bayesian: Domain-Invariant Learning with Uncertainty Zehao Xiao Jiayi Shen Xiantong Zhen Ling Shao Cees G. M. Snoek BDL UQCV OOD 29 39 0 09 May 2021
Exploring Uncertainty in Deep Learning for Construction of Prediction Intervals Yuandu Lai Yucheng Shi Yahong Han Yunfeng Shao Meiyu Qi Bingshuai Li UQCV 35 15 0 27 Apr 2021
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure Samuel Kim Peter Y. Lu Charlotte Loh Jamie Smith Jasper Snoek M. Soljavcić BDL AI4CE 100 17 0 23 Apr 2021
Accurate and Reliable Forecasting using Stochastic Differential Equations Peng Cui Zhijie Deng Wenbo Hu Jun Zhu UQCV 38 1 0 28 Mar 2021
LiBRe: A Practical Bayesian Approach to Adversarial Detection Zhijie Deng Xiao Yang Shizhen Xu Hang Su Jun Zhu BDL AAML 20 61 0 27 Mar 2021
Contextual Dropout: An Efficient Sample-Dependent Dropout Module Xinjie Fan Shujian Zhang Korawat Tanwisuth Xiaoning Qian Mingyuan Zhou OOD BDL UQCV 30 27 0 06 Mar 2021
Posterior Meta-Replay for Continual Learning Christian Henning Maria R. Cervera Francesco DÁngelo J. Oswald Regina Traber Benjamin Ehret Seijin Kobayashi Benjamin Grewe João Sacramento CLL BDL 51 54 0 01 Mar 2021
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations Winnie Xu Ricky T. Q. Chen Xuechen Li David Duvenaud BDL UQCV 27 46 0 12 Feb 2021
U-LanD: Uncertainty-Driven Video Landmark Detection Mohammad Jafari C. Luong Michael Y. Tsang A. Gu N. V. Woudenberg R. Rohling T. Tsang Purang Abolmaesumi 37 12 0 02 Feb 2021
Multidimensional Uncertainty-Aware Evidential Neural Networks Yibo Hu Yuzhe Ou Xujiang Zhao Jin-Hee Cho Feng Chen EDL UQCV AAML 33 23 0 26 Dec 2020
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data Lingkai Kong Haoming Jiang Yuchen Zhuang Jie Lyu T. Zhao Chao Zhang OODD 24 26 0 22 Oct 2020
Failure Prediction by Confidence Estimation of Uncertainty-Aware Dirichlet Networks Theodoros Tsiligkaridis UQCV 22 7 0 19 Oct 2020
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 19 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