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Deep Kernel Learning

Deep Kernel Learning

6 November 2015
A. Wilson
Zhiting Hu
Ruslan Salakhutdinov
Eric P. Xing
    BDL
ArXivPDFHTML

Papers citing "Deep Kernel Learning"

50 / 176 papers shown
Title
Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective
Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective
Hechuan Wen
Tong Chen
Mingming Gong
Li Kheng Chai
S. Sadiq
Hongzhi Yin
CML
58
0
0
08 May 2025
Conditional Diffusion-Based Retrieval of Atmospheric CO2 from Earth Observing Spectroscopy
Conditional Diffusion-Based Retrieval of Atmospheric CO2 from Earth Observing Spectroscopy
William R. Keely
Otto Lamminpää
Steffen Mauceri
Sean M. R. Crowell
Christopher W. O'Dell
Gregory R. McGarragh
55
0
0
23 Apr 2025
Latent Bayesian Optimization via Autoregressive Normalizing Flows
Latent Bayesian Optimization via Autoregressive Normalizing Flows
Seunghun Lee
Jinyoung Park
Jaewon Chu
Minseo Yoon
H. Kim
BDL
38
1
0
21 Apr 2025
GOLLuM: Gaussian Process Optimized LLMs -- Reframing LLM Finetuning through Bayesian Optimization
GOLLuM: Gaussian Process Optimized LLMs -- Reframing LLM Finetuning through Bayesian Optimization
Bojana Ranković
P. Schwaller
BDL
196
0
0
08 Apr 2025
Sparse Gaussian Neural Processes
Sparse Gaussian Neural Processes
Tommy Rochussen
Vincent Fortuin
BDL
UQCV
61
0
0
02 Apr 2025
SEEK: Self-adaptive Explainable Kernel For Nonstationary Gaussian Processes
SEEK: Self-adaptive Explainable Kernel For Nonstationary Gaussian Processes
Nima Negarandeh
Carlos Mora
Ramin Bostanabad
55
0
0
18 Mar 2025
Learning Stochastic Nonlinear Dynamics with Embedded Latent Transfer Operators
Learning Stochastic Nonlinear Dynamics with Embedded Latent Transfer Operators
Naichang Ke
Ryogo Tanaka
Yoshinobu Kawahara
34
0
0
06 Jan 2025
Image Classification with Deep Reinforcement Active Learning
Image Classification with Deep Reinforcement Active Learning
Mingyuan Jiu
Xuguang Song
H. Sahbi
Shupan Li
Yan Chen
Wei Guo
Lihua Guo
Mingliang Xu
VLM
29
0
0
31 Dec 2024
Compactly-supported nonstationary kernels for computing exact Gaussian processes on big data
Compactly-supported nonstationary kernels for computing exact Gaussian processes on big data
M. Risser
M. Noack
Hengrui Luo
Ronald Pandolfi
GP
33
0
0
07 Nov 2024
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning
Peter Eckmann
D. Wu
G. Heinzelmann
Michael K. Gilson
Rose Yu
AI4CE
42
0
0
15 Oct 2024
Federated Neural Nonparametric Point Processes
Federated Neural Nonparametric Point Processes
Hui Chen
Hengyu Liu
Hengyu Liu
Xuhui Fan
Zhilin Zhao
Feng Zhou
Christopher J. Quinn
Longbing Cao
FedML
43
0
0
08 Oct 2024
Lightning UQ Box: A Comprehensive Framework for Uncertainty
  Quantification in Deep Learning
Lightning UQ Box: A Comprehensive Framework for Uncertainty Quantification in Deep Learning
Nils Lehmann
Jakob Gawlikowski
Adam J. Stewart
Vytautas Jancauskas
Stefan Depeweg
Eric T. Nalisnick
N. Gottschling
42
0
0
04 Oct 2024
Deep Kernel Posterior Learning under Infinite Variance Prior Weights
Deep Kernel Posterior Learning under Infinite Variance Prior Weights
Jorge Loría
A. Bhadra
BDL
UQCV
66
0
0
02 Oct 2024
Learning Deep Kernels for Non-Parametric Independence Testing
Learning Deep Kernels for Non-Parametric Independence Testing
Nathaniel Xu
Feng Liu
Danica J. Sutherland
BDL
34
0
0
10 Sep 2024
Bayesian meta learning for trustworthy uncertainty quantification
Bayesian meta learning for trustworthy uncertainty quantification
Zhenyuan Yuan
Thinh T. Doan
UQCV
43
0
0
27 Jul 2024
OCCAM: Online Continuous Controller Adaptation with Meta-Learned Models
OCCAM: Online Continuous Controller Adaptation with Meta-Learned Models
Hersh Sanghvi
Spencer Folk
Camillo J Taylor
45
3
0
25 Jun 2024
Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise
Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise
T. Pouplin
Alan Jeffares
Nabeel Seedat
Mihaela van der Schaar
58
3
0
05 Jun 2024
Recurrent Deep Kernel Learning of Dynamical Systems
Recurrent Deep Kernel Learning of Dynamical Systems
N. Botteghi
Paolo Motta
Andrea Manzoni
P. Zunino
Mengwu Guo
33
1
0
30 May 2024
Infinite-Dimensional Feature Interaction
Infinite-Dimensional Feature Interaction
Chenhui Xu
Fuxun Yu
Maoliang Li
Zihao Zheng
Zirui Xu
Jinjun Xiong
Xiang Chen
42
1
0
22 May 2024
Spectral complexity of deep neural networks
Spectral complexity of deep neural networks
Simmaco Di Lillo
Domenico Marinucci
Michele Salvi
Stefano Vigogna
BDL
82
1
0
15 May 2024
Explainable Learning with Gaussian Processes
Explainable Learning with Gaussian Processes
Kurt Butler
Guanchao Feng
P. Djuric
39
1
0
11 Mar 2024
Kernel PCA for Out-of-Distribution Detection
Kernel PCA for Out-of-Distribution Detection
Kun Fang
Qinghua Tao
Kexin Lv
M. He
Xiaolin Huang
Jie-jin Yang
OODD
54
2
0
05 Feb 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
32
3
0
16 Jan 2024
Hybrid Modeling Design Patterns
Hybrid Modeling Design Patterns
Maja Rudolph
Stefan Kurz
Barbara Rakitsch
AI4CE
31
8
0
29 Dec 2023
Clairvoyance: A Pipeline Toolkit for Medical Time Series
Clairvoyance: A Pipeline Toolkit for Medical Time Series
Daniel Jarrett
Jinsung Yoon
Ioana Bica
Zhaozhi Qian
A. Ercole
M. Schaar
AI4TS
29
35
0
28 Oct 2023
RTDK-BO: High Dimensional Bayesian Optimization with Reinforced
  Transformer Deep kernels
RTDK-BO: High Dimensional Bayesian Optimization with Reinforced Transformer Deep kernels
Alexander Shmakov
Avisek Naug
Vineet Gundecha
Sahand Ghorbanpour
Ricardo Luna Gutierrez
Ashwin Ramesh Babu
Antonio Guillen-Perez
Soumyendu Sarkar
29
11
0
05 Oct 2023
Parallel and Limited Data Voice Conversion Using Stochastic Variational
  Deep Kernel Learning
Parallel and Limited Data Voice Conversion Using Stochastic Variational Deep Kernel Learning
Mohamadreza Jafaryani
H. Sheikhzadeh
V. Pourahmadi
19
4
0
08 Sep 2023
Learning Regions of Interest for Bayesian Optimization with Adaptive
  Level-Set Estimation
Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation
Fengxue Zhang
Jialin Song
James Bowden
Alexander Ladd
Yisong Yue
Thomas Desautels
Yuxin Chen
30
6
0
25 Jul 2023
FaIRGP: A Bayesian Energy Balance Model for Surface Temperatures
  Emulation
FaIRGP: A Bayesian Energy Balance Model for Surface Temperatures Emulation
S. Bouabid
Dino Sejdinovic
D. Watson‐Parris
16
5
0
14 Jul 2023
Large-Batch, Iteration-Efficient Neural Bayesian Design Optimization
Large-Batch, Iteration-Efficient Neural Bayesian Design Optimization
Navid Ansari
Hans-Peter Seidel
Vahid Babaei
19
2
0
01 Jun 2023
Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks
Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks
Felix Jimenez
Matthias Katzfuss
BDL
UQCV
64
1
0
26 May 2023
The Representation Jensen-Shannon Divergence
The Representation Jensen-Shannon Divergence
J. Hoyos-Osorio
Santiago Posso-Murillo
L. S. Giraldo
40
6
0
25 May 2023
Inverse Protein Folding Using Deep Bayesian Optimization
Inverse Protein Folding Using Deep Bayesian Optimization
Natalie Maus
Yimeng Zeng
Daniel A. Anderson
Phillip M. Maffettone
Aaron C. Solomon
Peyton Greenside
Osbert Bastani
Jacob R. Gardner
28
2
0
25 May 2023
Deep Pipeline Embeddings for AutoML
Deep Pipeline Embeddings for AutoML
Sebastian Pineda Arango
Josif Grabocka
36
2
0
23 May 2023
Error Analysis of Kernel/GP Methods for Nonlinear and Parametric PDEs
Error Analysis of Kernel/GP Methods for Nonlinear and Parametric PDEs
Pau Batlle
Yifan Chen
Bamdad Hosseini
H. Owhadi
Andrew M. Stuart
34
17
0
08 May 2023
Gaussian process deconvolution
Gaussian process deconvolution
Felipe A. Tobar
Arnaud Robert
Jorge F. Silva
33
5
0
08 May 2023
Uncertainty Quantification in Machine Learning for Engineering Design
  and Health Prognostics: A Tutorial
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial
V. Nemani
Luca Biggio
Xun Huan
Zhen Hu
Olga Fink
Anh Tran
Yan Wang
Xiaoge Zhang
Chao Hu
AI4CE
33
75
0
07 May 2023
Experience-Based Evolutionary Algorithms for Expensive Optimization
Experience-Based Evolutionary Algorithms for Expensive Optimization
Xunzhao Yu
Yan Wang
Ling Zhu
Dimitar Filev
Xin Yao
14
2
0
09 Apr 2023
Self-Distillation for Gaussian Process Regression and Classification
Self-Distillation for Gaussian Process Regression and Classification
Kenneth Borup
L. Andersen
11
2
0
05 Apr 2023
A dynamic Bayesian optimized active recommender system for
  curiosity-driven Human-in-the-loop automated experiments
A dynamic Bayesian optimized active recommender system for curiosity-driven Human-in-the-loop automated experiments
Arpan Biswas
Yongtao Liu
Nicole Creange
Yu-Chen Liu
S. Jesse
Jan-Chi Yang
Sergei V. Kalinin
M. Ziatdinov
Rama K Vasudevan
18
5
0
05 Apr 2023
Deep Ranking Ensembles for Hyperparameter Optimization
Deep Ranking Ensembles for Hyperparameter Optimization
Abdus Salam Khazi
Sebastian Pineda Arango
Josif Grabocka
BDL
39
7
0
27 Mar 2023
Interactive Segmentation as Gaussian Process Classification
Interactive Segmentation as Gaussian Process Classification
Minghao Zhou
Hong Wang
Qian Zhao
Yuexiang Li
Yawen Huang
Deyu Meng
Yefeng Zheng
VLM
26
22
0
28 Feb 2023
Transfer Learning for Bayesian Optimization: A Survey
Transfer Learning for Bayesian Optimization: A Survey
Tianyi Bai
Yang Li
Yu Shen
Xinyi Zhang
Wentao Zhang
Bin Cui
BDL
39
29
0
12 Feb 2023
Multi-view Kernel PCA for Time series Forecasting
Multi-view Kernel PCA for Time series Forecasting
Arun Pandey
Hannes De Meulemeester
B. De Moor
Johan A. K. Suykens
AI4TS
36
5
0
24 Jan 2023
Towards Flexibility and Interpretability of Gaussian Process State-Space
  Model
Towards Flexibility and Interpretability of Gaussian Process State-Space Model
Zhidi Lin
Feng Yin
Juan Maroñas
34
7
0
21 Jan 2023
Uncertainty in Real-Time Semantic Segmentation on Embedded Systems
Uncertainty in Real-Time Semantic Segmentation on Embedded Systems
Ethan Goan
Clinton Fookes
UQCV
31
4
0
20 Dec 2022
Faithful Heteroscedastic Regression with Neural Networks
Faithful Heteroscedastic Regression with Neural Networks
Andrew Stirn
H. Wessels
Megan D. Schertzer
L. Pereira
Neville E. Sanjana
David A. Knowles
UQCV
30
14
0
18 Dec 2022
Deep Kernel Learning for Mortality Prediction in the Face of Temporal
  Shift
Deep Kernel Learning for Mortality Prediction in the Face of Temporal Shift
Miguel Rios
A. Abu-Hanna
OOD
24
1
0
01 Dec 2022
Synthetic data enable experiments in atomistic machine learning
Synthetic data enable experiments in atomistic machine learning
John L A Gardner
Z. Beaulieu
Volker L. Deringer
37
6
0
29 Nov 2022
Counterfactual Learning with Multioutput Deep Kernels
Counterfactual Learning with Multioutput Deep Kernels
A. Caron
G. Baio
I. Manolopoulou
BDL
CML
OffRL
25
1
0
20 Nov 2022
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