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1810.03052
Cited By
Deep convolutional Gaussian processes
6 October 2018
Kenneth Blomqvist
Samuel Kaski
Markus Heinonen
BDL
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Papers citing
"Deep convolutional Gaussian processes"
38 / 38 papers shown
Deep Q-Exponential Processes
Symposium on Advances in Approximate Bayesian Inference (AABI), 2024
Zhi Chang
Chukwudi Obite
Shuang Zhou
Shiwei Lan
BDL
256
0
0
29 Oct 2024
Gaussian Process Model with Tensorial Inputs and Its Application to the Design of 3D Printed Antennas
Xi Chen
Yashika Sharma
Hao Helen Zhang
Xin Hao
Qiang Zhou
99
0
0
19 Jul 2024
Sparse Variational Student-t Processes
AAAI Conference on Artificial Intelligence (AAAI), 2023
Jian Xu
Delu Zeng
334
4
0
09 Dec 2023
Deep Latent Force Models: ODE-based Process Convolutions for Bayesian Deep Learning
Machine-mediated learning (ML), 2023
Thomas Baldwin-McDonald
Mauricio A. Álvarez
335
1
0
24 Nov 2023
Neural Operator Variational Inference based on Regularized Stein Discrepancy for Deep Gaussian Processes
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
Jian Xu
Shian Du
Junmei Yang
Qianli Ma
Delu Zeng
BDL
348
4
0
22 Sep 2023
A Unifying Perspective on Non-Stationary Kernels for Deeper Gaussian Processes
APL Machine Learning (AML), 2023
M. Noack
Hengrui Luo
M. Risser
GP
355
15
0
18 Sep 2023
Convolutional Deep Kernel Machines
International Conference on Learning Representations (ICLR), 2023
Edward Milsom
Ben Anson
Laurence Aitchison
BDL
481
5
0
18 Sep 2023
Gaussian process deconvolution
Proceedings of the Royal Society A (Proc. R. Soc. A), 2023
Felipe A. Tobar
Arnaud Robert
Jorge F. Silva
181
7
0
08 May 2023
Distributional Gaussian Processes Layers for Out-of-Distribution Detection
S. Popescu
D. Sharp
James H. Cole
Konstantinos Kamnitsas
Ben Glocker
OOD
280
1
0
27 Jun 2022
Shallow and Deep Nonparametric Convolutions for Gaussian Processes
Thomas M. McDonald
M. Ross
M. Smith
Mauricio A. Alvarez
143
1
0
17 Jun 2022
Geometry-Aware Hierarchical Bayesian Learning on Manifolds
IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2021
Yonghui Fan
Yalin Wang
213
2
0
30 Oct 2021
Wasserstein-Splitting Gaussian Process Regression for Heterogeneous Online Bayesian Inference
IEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2021
Michael E. Kepler
Alec Koppel
Amrit Singh Bedi
D. Stilwell
138
4
0
26 Jul 2021
An Analytical Survey on Recent Trends in High Dimensional Data Visualization
Alex B. Kiefer
Md. Khaledur Rahman
AI4TS
93
3
0
05 Jul 2021
The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective
Neural Information Processing Systems (NeurIPS), 2021
Geoff Pleiss
John P. Cunningham
246
30
0
11 Jun 2021
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
International Conference on Machine Learning (ICML), 2021
Shengyang Sun
Jiaxin Shi
A. Wilson
Roger C. Grosse
BDL
103
8
0
10 Jun 2021
Priors in Bayesian Deep Learning: A Review
International Statistical Review (ISR), 2021
Vincent Fortuin
UQCV
BDL
444
159
0
14 May 2021
Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation
Information Processing in Medical Imaging (IPMI), 2021
S. Popescu
D. Sharp
James H. Cole
Konstantinos Kamnitsas
Ben Glocker
99
5
0
28 Apr 2021
GPflux: A Library for Deep Gaussian Processes
Vincent Dutordoir
Hugh Salimbeni
Eric Hambro
John Mcleod
Felix Leibfried
A. Artemev
Mark van der Wilk
J. Hensman
M. Deisenroth
S. T. John
GP
211
29
0
12 Apr 2021
A Tutorial on Sparse Gaussian Processes and Variational Inference
Felix Leibfried
Vincent Dutordoir
S. T. John
N. Durrande
GP
1.2K
62
0
27 Dec 2020
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges
Information Fusion (Inf. Fusion), 2020
Moloud Abdar
Farhad Pourpanah
Sadiq Hussain
Dana Rezazadegan
Tianpeng Liu
...
Xiaochun Cao
Abbas Khosravi
U. Acharya
V. Makarenkov
S. Nahavandi
BDL
UQCV
955
2,296
0
12 Nov 2020
Pathwise Conditioning of Gaussian Processes
James T. Wilson
Viacheslav Borovitskiy
Alexander Terenin
P. Mostowsky
M. Deisenroth
465
70
0
08 Nov 2020
Hierarchical Gaussian Processes with Wasserstein-2 Kernels
S. Popescu
D. Sharp
James H. Cole
Ben Glocker
305
5
0
28 Oct 2020
Probabilistic selection of inducing points in sparse Gaussian processes
Conference on Uncertainty in Artificial Intelligence (UAI), 2020
Anders Kirk Uhrenholt
V. Charvet
B. S. Jensen
247
15
0
19 Oct 2020
Adaptive Signal Variances: CNN Initialization Through Modern Architectures
Takahiko Henmi
E. R. R. Zara
Yoshihiro Hirohashi
Tsuyoshi Kato
197
3
0
16 Aug 2020
DeepKriging: Spatially Dependent Deep Neural Networks for Spatial Prediction
Statistica sinica (SS), 2020
Wanfang Chen
Yuxiao Li
Brian J. Reich
Ying Sun
229
43
0
23 Jul 2020
Deep covariate-learning: optimising information extraction from terrain texture for geostatistical modelling applications
Charlie Kirkwood
138
4
0
22 May 2020
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes
Sebastian W. Ober
Laurence Aitchison
BDL
606
62
0
17 May 2020
Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations
Simone Rossi
Markus Heinonen
Edwin V. Bonilla
Zheyan Shen
Maurizio Filippone
UQCV
BDL
372
0
0
06 Mar 2020
A Framework for Interdomain and Multioutput Gaussian Processes
Mark van der Wilk
Vincent Dutordoir
S. T. John
A. Artemev
Vincent Adam
J. Hensman
257
100
0
02 Mar 2020
Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019
Pablo Morales-Álvarez
Pablo Ruiz
S. Coughlin
Rafael Molina
Aggelos K. Katsaggelos
179
16
0
05 Nov 2019
Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes
Neural Information Processing Systems (NeurIPS), 2019
Greg Yang
483
220
0
28 Oct 2019
A Fine-Grained Spectral Perspective on Neural Networks
Greg Yang
Hadi Salman
377
117
0
24 Jul 2019
On Exact Computation with an Infinitely Wide Neural Net
Sanjeev Arora
S. Du
Wei Hu
Zhiyuan Li
Ruslan Salakhutdinov
Ruosong Wang
641
991
0
26 Apr 2019
Bayesian Image Classification with Deep Convolutional Gaussian Processes
Vincent Dutordoir
Mark van der Wilk
A. Artemev
J. Hensman
UQCV
BDL
290
36
0
15 Feb 2019
Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation
Greg Yang
511
296
0
13 Feb 2019
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes
Roman Novak
Lechao Xiao
Jaehoon Lee
Yasaman Bahri
Greg Yang
Jiri Hron
Daniel A. Abolafia
Jeffrey Pennington
Jascha Narain Sohl-Dickstein
UQCV
BDL
332
324
0
11 Oct 2018
Posterior Inference for Sparse Hierarchical Non-stationary Models
K. Monterrubio-Gómez
L. Roininen
S. Wade
Theo Damoulas
Mark Girolami
272
27
0
04 Apr 2018
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
Leland McInnes
John Healy
James Melville
986
11,283
0
09 Feb 2018
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