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1707.05922
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Improving Output Uncertainty Estimation and Generalization in Deep Learning via Neural Network Gaussian Processes
19 July 2017
Tomoharu Iwata
Zoubin Ghahramani
UQCV
BDL
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Papers citing
"Improving Output Uncertainty Estimation and Generalization in Deep Learning via Neural Network Gaussian Processes"
24 / 24 papers shown
Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks
Kyung-Hwan Lee
Kyung-Tae Kim
250
0
0
21 Jul 2025
Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks
Debargha Ganguly
Vikash Singh
Sreehari Sankar
Biyao Zhang
Xuecen Zhang
Srinivasan Iyengar
Xiaotian Han
Amit Sharma
Shivkumar Kalyanaraman
Vipin Chaudhary
462
7
0
26 May 2025
SEEK: Self-adaptive Explainable Kernel For Nonstationary Gaussian Processes
Nima Negarandeh
Carlos Mora
Ramin Bostanabad
367
1
0
18 Mar 2025
A Survey of Uncertainty Estimation in LLMs: Theory Meets Practice
Hsiu-Yuan Huang
Yutong Yang
Zhaoxi Zhang
Sanwoo Lee
Yunfang Wu
498
43
0
20 Oct 2024
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
International Conference on Learning Representations (ICLR), 2024
Jasmine Bayrooti
Carl Henrik Ek
Amanda Prorok
525
4
0
07 Oct 2024
Photoelectric Factor Prediction Using Automated Learning and Uncertainty Quantification
K. Alsamadony
A. Ibrahim
S. Elkatatny
A. Abdulraheem
177
2
0
17 Jun 2022
Bayesian Model Selection, the Marginal Likelihood, and Generalization
International Conference on Machine Learning (ICML), 2022
Sanae Lotfi
Pavel Izmailov
Gregory W. Benton
Micah Goldblum
A. Wilson
UQCV
BDL
542
80
0
23 Feb 2022
Dynamic Combination of Heterogeneous Models for Hierarchical Time Series
Xing Han
Jing Hu
Joydeep Ghosh
AI4TS
270
5
0
22 Dec 2021
Priors in Bayesian Deep Learning: A Review
International Statistical Review (ISR), 2021
Vincent Fortuin
UQCV
BDL
570
169
0
14 May 2021
Calibrated simplex-mapping classification
PLoS ONE (PLOS ONE), 2021
R. Heese
J. Schmid
Michal Walczak
Michael Bortz
304
4
0
04 Mar 2021
Simultaneously Reconciled Quantile Forecasting of Hierarchically Related Time Series
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Xing Han
S. Dasgupta
Joydeep Ghosh
AI4TS
259
39
0
25 Feb 2021
A Novel Regression Loss for Non-Parametric Uncertainty Optimization
Joachim Sicking
Maram Akila
Maximilian Pintz
Tim Wirtz
Asja Fischer
Stefan Wrobel
UQCV
201
3
0
07 Jan 2021
Wasserstein Dropout
Machine-mediated learning (ML), 2020
Joachim Sicking
Maram Akila
Maximilian Pintz
Tim Wirtz
Asja Fischer
Stefanie Wrobel
BDL
OOD
UQCV
305
3
0
23 Dec 2020
Few-shot Learning for Spatial Regression
Machine-mediated learning (ML), 2020
Tomoharu Iwata
Yusuke Tanaka
360
13
0
09 Oct 2020
Fast Deep Mixtures of Gaussian Process Experts
Machine-mediated learning (ML), 2020
Clement Etienam
K. Law
S. Wade
Vitaly Zankin
423
6
0
11 Jun 2020
Deep Latent-Variable Kernel Learning
Haitao Liu
Yew-Soon Ong
Xiaomo Jiang
Xiaofang Wang
BDL
254
9
0
18 May 2020
What do you Mean? The Role of the Mean Function in Bayesian Optimisation
George De Ath
J. Fieldsend
Richard Everson
275
20
0
17 Apr 2020
On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation
N. Brosse
C. Riquelme
Alice Martin
Sylvain Gelly
Eric Moulines
BDL
OOD
UQCV
281
36
0
22 Jan 2020
Efficient Transfer Bayesian Optimization with Auxiliary Information
Tomoharu Iwata
Takuma Otsuka
232
2
0
17 Sep 2019
Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel
International Conference on Learning Representations (ICLR), 2019
Xin Qiu
Elliot Meyerson
Risto Miikkulainen
UQCV
425
59
0
03 Jun 2019
Meta-Learning Mean Functions for Gaussian Processes
Vincent Fortuin
Heiko Strathmann
Gunnar Rätsch
BDL
FedML
MLT
652
33
0
23 Jan 2019
When Gaussian Process Meets Big Data: A Review of Scalable GPs
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2018
Haitao Liu
Yew-Soon Ong
Xiaobo Shen
Jianfei Cai
GP
570
846
0
03 Jul 2018
Variational Implicit Processes
Chao Ma
Yingzhen Li
José Miguel Hernández-Lobato
BDL
369
75
0
06 Jun 2018
Deep Mixed Effect Model using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare
Ingyo Chung
Saehoon Kim
Juho Lee
Kwang Joon Kim
Sung Ju Hwang
Eunho Yang
BDL
FedML
282
21
0
05 Jun 2018
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