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Weight Uncertainty in Neural Networks

Weight Uncertainty in Neural Networks

20 May 2015
Charles Blundell
Julien Cornebise
Koray Kavukcuoglu
Daan Wierstra
    UQCV
    BDL
ArXivPDFHTML

Papers citing "Weight Uncertainty in Neural Networks"

50 / 396 papers shown
Title
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label
  Selection Framework for Semi-Supervised Learning
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning
Mamshad Nayeem Rizve
Kevin Duarte
Yogesh S Rawat
M. Shah
247
510
0
15 Jan 2021
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial
  Estimation
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation
Alexandre Ramé
Matthieu Cord
FedML
56
51
0
14 Jan 2021
Bayesian neural networks for weak solution of PDEs with uncertainty
  quantification
Bayesian neural networks for weak solution of PDEs with uncertainty quantification
Xiaoxuan Zhang
K. Garikipati
AI4CE
46
11
0
13 Jan 2021
On the Calibration and Uncertainty of Neural Learning to Rank Models
On the Calibration and Uncertainty of Neural Learning to Rank Models
Gustavo Penha
C. Hauff
190
30
0
12 Jan 2021
Minimum Excess Risk in Bayesian Learning
Minimum Excess Risk in Bayesian Learning
Aolin Xu
Maxim Raginsky
36
38
0
29 Dec 2020
A Tutorial on Sparse Gaussian Processes and Variational Inference
A Tutorial on Sparse Gaussian Processes and Variational Inference
Felix Leibfried
Vincent Dutordoir
S. T. John
N. Durrande
GP
42
49
0
27 Dec 2020
Multidimensional Uncertainty-Aware Evidential Neural Networks
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
An Active Learning Method for Diabetic Retinopathy Classification with
  Uncertainty Quantification
An Active Learning Method for Diabetic Retinopathy Classification with Uncertainty Quantification
Muhammad Ahtazaz Ahsan
A. Qayyum
Junaid Qadir
Adeel Razi
BDL
23
19
0
24 Dec 2020
On Batch Normalisation for Approximate Bayesian Inference
On Batch Normalisation for Approximate Bayesian Inference
Jishnu Mukhoti
P. Dokania
Philip Torr
Y. Gal
BDL
UQCV
29
4
0
24 Dec 2020
Objective Evaluation of Deep Uncertainty Predictions for COVID-19
  Detection
Objective Evaluation of Deep Uncertainty Predictions for COVID-19 Detection
Hamzeh Asgharnezhad
Afshar Shamsi Jokandan
R. Alizadehsani
Abbas Khosravi
S. Nahavandi
Z. Sani
D. Srinivasan
UQCV
36
70
0
22 Dec 2020
Towards Trustworthy Predictions from Deep Neural Networks with Fast
  Adversarial Calibration
Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration
Christian Tomani
Florian Buettner
UQCV
AAML
OOD
27
39
0
20 Dec 2020
Learning Prediction Intervals for Model Performance
Learning Prediction Intervals for Model Performance
Benjamin Elder
Matthew Arnold
Anupama Murthi
Jirí Navrátil
27
10
0
15 Dec 2020
Uncertainty Estimation with Deep Learning for Rainfall-Runoff Modelling
Uncertainty Estimation with Deep Learning for Rainfall-Runoff Modelling
D. Klotz
Frederik Kratzert
M. Gauch
A. Sampson
Günter Klambauer
Sepp Hochreiter
G. Nearing
BDL
UQCV
18
106
0
15 Dec 2020
Confidence Estimation via Auxiliary Models
Confidence Estimation via Auxiliary Models
Charles Corbière
Nicolas Thome
A. Saporta
Tuan-Hung Vu
Matthieu Cord
P. Pérez
TPM
29
47
0
11 Dec 2020
Know Your Limits: Uncertainty Estimation with ReLU Classifiers Fails at
  Reliable OOD Detection
Know Your Limits: Uncertainty Estimation with ReLU Classifiers Fails at Reliable OOD Detection
Dennis Ulmer
Giovanni Cina
OODD
35
31
0
09 Dec 2020
Mix and Match: A Novel FPGA-Centric Deep Neural Network Quantization
  Framework
Mix and Match: A Novel FPGA-Centric Deep Neural Network Quantization Framework
Sung-En Chang
Yanyu Li
Mengshu Sun
Runbin Shi
Hayden Kwok-Hay So
Xuehai Qian
Yanzhi Wang
Xue Lin
MQ
26
83
0
08 Dec 2020
Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks
  for Accurate and Precise Inference of the Hubble Constant
Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant
Ji Won Park
S. Wagner-Carena
S. Birrer
P. Marshall
J. Lin
A. Roodman
3DV
16
24
0
30 Nov 2020
Exploration in Online Advertising Systems with Deep Uncertainty-Aware
  Learning
Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning
Chao Du
Zhifeng Gao
Shuo Yuan
Lining Gao
Z. Li
Yifan Zeng
Xiaoqiang Zhu
Jian Xu
Kun Gai
Kuang-chih Lee
25
18
0
25 Nov 2020
Uncertainty Estimation and Calibration with Finite-State Probabilistic
  RNNs
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs
Cheng Wang
Carolin (Haas) Lawrence
Mathias Niepert
UQCV
29
10
0
24 Nov 2020
A Review and Comparative Study on Probabilistic Object Detection in
  Autonomous Driving
A Review and Comparative Study on Probabilistic Object Detection in Autonomous Driving
Di Feng
Ali Harakeh
Steven Waslander
Klaus C. J. Dietmayer
AAML
UQCV
EDL
24
224
0
20 Nov 2020
DS-UI: Dual-Supervised Mixture of Gaussian Mixture Models for
  Uncertainty Inference
DS-UI: Dual-Supervised Mixture of Gaussian Mixture Models for Uncertainty Inference
Jiyang Xie
Zhanyu Ma
Jing-Hao Xue
Guoqiang Zhang
Jun Guo
BDL
27
11
0
17 Nov 2020
Artificial Neural Variability for Deep Learning: On Overfitting, Noise
  Memorization, and Catastrophic Forgetting
Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting
Zeke Xie
Fengxiang He
Shaopeng Fu
Issei Sato
Dacheng Tao
Masashi Sugiyama
21
60
0
12 Nov 2020
Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD
  Detection On Medical Tabular Data
Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Data
Dennis Ulmer
L. Meijerink
Giovanni Cina
OOD
13
64
0
06 Nov 2020
Evaluating Robustness of Predictive Uncertainty Estimation: Are
  Dirichlet-based Models Reliable?
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?
Anna-Kathrin Kopetzki
Bertrand Charpentier
Daniel Zügner
Sandhya Giri
Stephan Günnemann
23
45
0
28 Oct 2020
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution
  Data
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
30
26
0
22 Oct 2020
Incorporating Interpretable Output Constraints in Bayesian Neural
  Networks
Incorporating Interpretable Output Constraints in Bayesian Neural Networks
Wanqian Yang
Lars Lorch
Moritz Graule
Himabindu Lakkaraju
Finale Doshi-Velez
UQCV
BDL
17
16
0
21 Oct 2020
Bayesian Attention Modules
Bayesian Attention Modules
Xinjie Fan
Shujian Zhang
Bo Chen
Mingyuan Zhou
117
59
0
20 Oct 2020
Failure Prediction by Confidence Estimation of Uncertainty-Aware
  Dirichlet Networks
Failure Prediction by Confidence Estimation of Uncertainty-Aware Dirichlet Networks
Theodoros Tsiligkaridis
UQCV
22
7
0
19 Oct 2020
Training independent subnetworks for robust prediction
Training independent subnetworks for robust prediction
Marton Havasi
Rodolphe Jenatton
Stanislav Fort
Jeremiah Zhe Liu
Jasper Snoek
Balaji Lakshminarayanan
Andrew M. Dai
Dustin Tran
UQCV
OOD
41
208
0
13 Oct 2020
Neural Thompson Sampling
Neural Thompson Sampling
Weitong Zhang
Dongruo Zhou
Lihong Li
Quanquan Gu
34
115
0
02 Oct 2020
Why have a Unified Predictive Uncertainty? Disentangling it using Deep
  Split Ensembles
Why have a Unified Predictive Uncertainty? Disentangling it using Deep Split Ensembles
U. Sarawgi
W. Zulfikar
Rishab Khincha
Pattie Maes
PER
UQCV
BDL
UD
21
7
0
25 Sep 2020
Propensity-to-Pay: Machine Learning for Estimating Prediction
  Uncertainty
Propensity-to-Pay: Machine Learning for Estimating Prediction Uncertainty
M. A. Bashar
Kieren Astin-Walmsley
Kerina Heath
R. Nayak
24
2
0
27 Aug 2020
Beyond Point Estimate: Inferring Ensemble Prediction Variation from
  Neuron Activation Strength in Recommender Systems
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
31
16
0
17 Aug 2020
Survey of XAI in digital pathology
Survey of XAI in digital pathology
Milda Pocevičiūtė
Gabriel Eilertsen
Claes Lundström
14
56
0
14 Aug 2020
Interpretable Sequence Learning for COVID-19 Forecasting
Interpretable Sequence Learning for COVID-19 Forecasting
Sercan Ö. Arik
Chun-Liang Li
Jinsung Yoon
Rajarishi Sinha
Arkady Epshteyn
...
Martin Nikoltchev
Yash Sonthalia
Hootan Nakhost
Elli Kanal
Tomas Pfister
AI4TS
28
83
0
03 Aug 2020
Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal
  Relational Learning
Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning
Wentao Bao
Qi Yu
Yu Kong
35
132
0
01 Aug 2020
Tighter risk certificates for neural networks
Tighter risk certificates for neural networks
Maria Perez-Ortiz
Omar Rivasplata
John Shawe-Taylor
Csaba Szepesvári
UQCV
20
102
0
25 Jul 2020
Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma
  Augmented Gaussian Processes
Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes
Jake C. Snell
R. Zemel
33
63
0
20 Jul 2020
Contrastive Training for Improved Out-of-Distribution Detection
Contrastive Training for Improved Out-of-Distribution Detection
Jim Winkens
Rudy Bunel
Abhijit Guha Roy
Robert Stanforth
Vivek Natarajan
...
Alan Karthikesalingam
Simon A. A. Kohl
taylan. cemgil
S. M. Ali Eslami
Olaf Ronneberger
OODD
19
236
0
10 Jul 2020
Quantifying and Leveraging Predictive Uncertainty for Medical Image
  Assessment
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
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
Hyperparameter Ensembles for Robustness and Uncertainty Quantification
Hyperparameter Ensembles for Robustness and Uncertainty Quantification
F. Wenzel
Jasper Snoek
Dustin Tran
Rodolphe Jenatton
UQCV
33
204
0
24 Jun 2020
PAC-Bayes Analysis Beyond the Usual Bounds
PAC-Bayes Analysis Beyond the Usual Bounds
Omar Rivasplata
Ilja Kuzborskij
Csaba Szepesvári
John Shawe-Taylor
33
80
0
23 Jun 2020
Bayesian Neural Networks: An Introduction and Survey
Bayesian Neural Networks: An Introduction and Survey
Ethan Goan
Clinton Fookes
BDL
UQCV
37
199
0
22 Jun 2020
Gradient-EM Bayesian Meta-learning
Gradient-EM Bayesian Meta-learning
Yayi Zou
Xiaoqi Lu
BDL
35
16
0
21 Jun 2020
Uncertainty-Aware (UNA) Bases for Deep Bayesian Regression Using
  Multi-Headed Auxiliary Networks
Uncertainty-Aware (UNA) Bases for Deep Bayesian Regression Using Multi-Headed Auxiliary Networks
Sujay Thakur
Cooper Lorsung
Yaniv Yacoby
Finale Doshi-Velez
Weiwei Pan
BDL
UQCV
33
4
0
21 Jun 2020
Estimating Model Uncertainty of Neural Networks in Sparse Information
  Form
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
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
Towards Adaptive Benthic Habitat Mapping
J. Shields
Oscar Pizarro
Stefan B. Williams
22
14
0
20 Jun 2020
Variational State-Space Models for Localisation and Dense 3D Mapping in
  6 DoF
Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF
Atanas Mirchev
Baris Kayalibay
Patrick van der Smagt
Justin Bayer
BDL
DRL
27
9
0
17 Jun 2020
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