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Kernel Identification Through Transformers
v1v2 (latest)

Kernel Identification Through Transformers

15 June 2021
F. Simpson
Ian Davies
V. Lalchand
A. Vullo
N. Durrande
C. Rasmussen
ArXiv (abs)PDFHTMLGithub (14★)

Papers citing "Kernel Identification Through Transformers"

11 / 11 papers shown
MIST: Mutual Information Estimation Via Supervised Training
MIST: Mutual Information Estimation Via Supervised Training
German Gritsai
Megan Richards
Maxime Méloux
Kyunghyun Cho
Maxime Peyrard
OOD
387
0
0
24 Nov 2025
Adaptive Kernel Design for Bayesian Optimization Is a Piece of CAKE with LLMs
Adaptive Kernel Design for Bayesian Optimization Is a Piece of CAKE with LLMs
Richard Cornelius Suwandi
Feng Yin
Juntao Wang
Renjie Li
Tsung-Hui Chang
Sergios Theodoridis
BDL
228
2
0
22 Sep 2025
Amortized In-Context Bayesian Posterior Estimation
Amortized In-Context Bayesian Posterior Estimation
Sarthak Mittal
Niels Leif Bracher
Guillaume Lajoie
P. Jaini
Marcus A. Brubaker
341
13
0
10 Feb 2025
Amortized Probabilistic Conditioning for Optimization, Simulation and Inference
Amortized Probabilistic Conditioning for Optimization, Simulation and InferenceInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Paul E. Chang
Nasrulloh Loka
Daolang Huang
Ulpu Remes
Samuel Kaski
Luigi Acerbi
AI4CE
445
21
0
20 Oct 2024
On the Identifiability and Interpretability of Gaussian Process Models
On the Identifiability and Interpretability of Gaussian Process ModelsNeural Information Processing Systems (NeurIPS), 2023
Jiawen Chen
W. Mu
Yun Li
Didong Li
271
7
0
25 Oct 2023
Beyond Intuition, a Framework for Applying GPs to Real-World Data
Beyond Intuition, a Framework for Applying GPs to Real-World Data
K. Tazi
J. Lin
Ross Viljoen
A. Gardner
S. T. John
Hong Ge
Richard Turner
GP
346
6
0
06 Jul 2023
Practical Equivariances via Relational Conditional Neural Processes
Practical Equivariances via Relational Conditional Neural ProcessesNeural Information Processing Systems (NeurIPS), 2023
Daolang Huang
Manuel Haussmann
Ulpu Remes
S. T. John
Grégoire Clarté
K. Luck
Samuel Kaski
Luigi Acerbi
BDL
496
12
0
19 Jun 2023
Amortized Inference for Gaussian Process Hyperparameters of Structured
  Kernels
Amortized Inference for Gaussian Process Hyperparameters of Structured KernelsConference on Uncertainty in Artificial Intelligence (UAI), 2023
M. Bitzer
Mona Meister
Christoph Zimmer
258
10
0
16 Jun 2023
MONGOOSE: Path-wise Smooth Bayesian Optimisation via Meta-learning
MONGOOSE: Path-wise Smooth Bayesian Optimisation via Meta-learning
Adam X. Yang
Laurence Aitchison
Henry B. Moss
364
6
0
22 Feb 2023
Gaussian Process Surrogate Models for Neural Networks
Gaussian Process Surrogate Models for Neural NetworksConference on Uncertainty in Artificial Intelligence (UAI), 2022
Michael Y. Li
Erin Grant
Thomas Griffiths
BDLSyDa
361
10
0
11 Aug 2022
Neural Diffusion Processes
Neural Diffusion ProcessesInternational Conference on Machine Learning (ICML), 2022
Vincent Dutordoir
Alan D. Saul
Zoubin Ghahramani
F. Simpson
DiffM
439
52
0
08 Jun 2022
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