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Meta-Learning Mean Functions for Gaussian Processes
v1v2v3v4 (latest)

Meta-Learning Mean Functions for Gaussian Processes

23 January 2019
Vincent Fortuin
Heiko Strathmann
Gunnar Rätsch
    BDLFedMLMLT
ArXiv (abs)PDFHTML

Papers citing "Meta-Learning Mean Functions for Gaussian Processes"

20 / 20 papers shown
Sparse Gaussian Neural Processes
Sparse Gaussian Neural ProcessesSymposium on Advances in Approximate Bayesian Inference (AABI), 2025
Tommy Rochussen
Vincent Fortuin
BDLUQCV
496
2
0
02 Apr 2025
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson SamplingInternational Conference on Learning Representations (ICLR), 2024
Jasmine Bayrooti
Carl Henrik Ek
Amanda Prorok
522
4
0
07 Oct 2024
Few-shot Scooping Under Domain Shift via Simulated Maximal Deployment
  Gaps
Few-shot Scooping Under Domain Shift via Simulated Maximal Deployment Gaps
Yifan Zhu
Pranay Thangeda
Erica Tevere
Ashish Goel
Erik Kramer
Hari Nayar
Melkior Ornik
Kris K. Hauser
278
0
0
06 Aug 2024
Personalized Federated Learning of Probabilistic Models: A PAC-Bayesian Approach
Personalized Federated Learning of Probabilistic Models: A PAC-Bayesian Approach
Mahrokh Ghoddousi Boroujeni
Andreas Krause
Giancarlo Ferrari-Trecate
FedML
439
11
0
16 Jan 2024
Meta-learning to Calibrate Gaussian Processes with Deep Kernels for
  Regression Uncertainty Estimation
Meta-learning to Calibrate Gaussian Processes with Deep Kernels for Regression Uncertainty Estimation
Tomoharu Iwata
Atsutoshi Kumagai
BDLUQCV
268
3
0
13 Dec 2023
Few-shot Adaptation for Manipulating Granular Materials Under Domain
  Shift
Few-shot Adaptation for Manipulating Granular Materials Under Domain Shift
Yifan Zhu
Pranay Thangeda
Melkior Ornik
Kris K. Hauser
374
18
0
06 Mar 2023
Environmental Sensor Placement with Convolutional Gaussian Neural
  Processes
Environmental Sensor Placement with Convolutional Gaussian Neural ProcessesEnvironmental Data Science (EDS), 2022
Tom R. Andersson
W. Bruinsma
Stratis Markou
James Requeima
Alejandro Coca-Castro
...
A. Ellis
M. Lazzara
Daniel P. Jones
Scott Hosking
Richard Turner
399
28
0
18 Nov 2022
MARS: Meta-Learning as Score Matching in the Function Space
MARS: Meta-Learning as Score Matching in the Function SpaceInternational Conference on Learning Representations (ICLR), 2022
Krunoslav Lehman Pavasovic
Jonas Rothfuss
Andreas Krause
BDL
469
7
0
24 Oct 2022
Meta-learning for Out-of-Distribution Detection via Density Estimation
  in Latent Space
Meta-learning for Out-of-Distribution Detection via Density Estimation in Latent Space
Tomoharu Iwata
Atsutoshi Kumagai
OODD
166
3
0
20 Jun 2022
End-to-End Learning of Deep Kernel Acquisition Functions for Bayesian
  Optimization
End-to-End Learning of Deep Kernel Acquisition Functions for Bayesian Optimization
Tomoharu Iwata
BDL
189
5
0
01 Nov 2021
Multi-Task Neural Processes
Multi-Task Neural Processes
Donggyun Kim
Seongwoong Cho
Wonkwang Lee
Seunghoon Hong
345
0
0
28 Oct 2021
Non-Gaussian Gaussian Processes for Few-Shot Regression
Non-Gaussian Gaussian Processes for Few-Shot Regression
Marcin Sendera
Jacek Tabor
A. Nowak
Andrzej Bedychaj
Massimiliano Patacchiola
Tomasz Trzciñski
Przemysław Spurek
Maciej Ziȩba
263
22
0
26 Oct 2021
Principal component analysis for Gaussian process posteriors
Principal component analysis for Gaussian process posteriorsNeural Computation (Neural Comput.), 2021
Hideaki Ishibashi
S. Akaho
328
7
0
15 Jul 2021
Transfer Bayesian Meta-learning via Weighted Free Energy Minimization
Transfer Bayesian Meta-learning via Weighted Free Energy MinimizationInternational Workshop on Machine Learning for Signal Processing (MLSP), 2021
Yunchuan Zhang
Sharu Theresa Jose
Osvaldo Simeone
271
0
0
20 Jun 2021
Priors in Bayesian Deep Learning: A Review
Priors in Bayesian Deep Learning: A ReviewInternational Statistical Review (ISR), 2021
Vincent Fortuin
UQCVBDL
551
167
0
14 May 2021
ALPaCA vs. GP-based Prior Learning: A Comparison between two Bayesian
  Meta-Learning Algorithms
ALPaCA vs. GP-based Prior Learning: A Comparison between two Bayesian Meta-Learning Algorithms
Yilun Wu
UQCVBDL
156
2
0
15 Oct 2020
Few-shot Learning for Spatial Regression
Few-shot Learning for Spatial RegressionMachine-mediated learning (ML), 2020
Tomoharu Iwata
Yusuke Tanaka
354
13
0
09 Oct 2020
What do you Mean? The Role of the Mean Function in Bayesian Optimisation
What do you Mean? The Role of the Mean Function in Bayesian Optimisation
George De Ath
J. Fieldsend
Richard Everson
262
20
0
17 Apr 2020
MGP-AttTCN: An Interpretable Machine Learning Model for the Prediction
  of Sepsis
MGP-AttTCN: An Interpretable Machine Learning Model for the Prediction of SepsisPLoS ONE (PLoS ONE), 2019
Margherita Rosnati
Vincent Fortuin
296
45
0
27 Sep 2019
Deep Mixed Effect Model using Gaussian Processes: A Personalized and
  Reliable Prediction for Healthcare
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
BDLFedML
273
21
0
05 Jun 2018
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