Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1705.08933
Cited By
v1
v2 (latest)
Doubly Stochastic Variational Inference for Deep Gaussian Processes
24 May 2017
Hugh Salimbeni
M. Deisenroth
BDL
GP
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Doubly Stochastic Variational Inference for Deep Gaussian Processes"
50 / 238 papers shown
Deep Gaussian Process Proximal Policy Optimization
Matthijs van der Lende
Juan Cardenas-Cartagena
GP
BDL
UQCV
387
0
0
22 Nov 2025
Deep Gaussian Processes for Functional Maps
Matthew Lowery
Zhitong Xu
D. Long
Keyan Chen
Daniel S. Johnson
Yang Bai
Varun Shankar
Shandian Zhe
AI4CE
128
0
0
24 Oct 2025
Diffusion Bridge Variational Inference for Deep Gaussian Processes
Jian Xu
Qibin Zhao
John Paisley
Delu Zeng
DiffM
213
0
0
23 Sep 2025
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
186
2
0
22 Sep 2025
Deep Gaussian Process-based Cost-Aware Batch Bayesian Optimization for Complex Materials Design Campaigns
Sk Md Ahnaf Akif Alvi
Brent Vela
V. Attari
Jan Janssen
Danny Perez
D. Allaire
Raymundo Arroyave
121
0
0
17 Sep 2025
Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks
Kyung-Hwan Lee
Kyung-Tae Kim
207
0
0
21 Jul 2025
Accurate and Uncertainty-Aware Multi-Task Prediction of HEA Properties Using Prior-Guided Deep Gaussian Processes
npj Computational Materials (npj Comput. Mater.), 2025
Sk Md Ahnaf Akif Alvi
Mrinalini Mulukutla
Nicolas Flores
Danial Khatamsaz
Jan Janssen
Danny Perez
D. Allaire
V. Attari
Raymundo Arroyave
AI4CE
131
2
0
13 Jun 2025
STACI: Spatio-Temporal Aleatoric Conformal Inference
Brandon Feng
David K. Park
Xihaier Luo
Arantxa Urdangarin
Shinjae Yoo
Brian J. Reich
201
0
0
27 May 2025
Active Learning for Multiple Change Point Detection in Non-stationary Time Series with Deep Gaussian Processes
Hao Zhao
Rong Pan
111
0
0
26 May 2025
Integrative Analysis and Imputation of Multiple Data Streams via Deep Gaussian Processes
Ali Akbar Septiandri
Deyu Ming
F. Alejandro DiazDelaO
Takoua Jendoubi
Samiran Ray
207
0
0
17 May 2025
Evaluating Uncertainty in Deep Gaussian Processes
Matthijs van der Lende
Jeremias Lino Ferrao
Niclas Müller-Hof
UQCV
235
1
0
24 Apr 2025
Stochastic Process Learning via Operator Flow Matching
Yaozhong Shi
Zachary E. Ross
D. Asimaki
Kamyar Azizzadenesheli
608
5
0
07 Jan 2025
Residual Deep Gaussian Processes on Manifolds
International Conference on Learning Representations (ICLR), 2024
Kacper Wyrwal
Andreas Krause
Viacheslav Borovitskiy
BDL
265
2
0
31 Oct 2024
Deep Q-Exponential Processes
Symposium on Advances in Approximate Bayesian Inference (AABI), 2024
Zhi Chang
Chukwudi Obite
Shuang Zhou
Shiwei Lan
BDL
262
0
0
29 Oct 2024
Hyperboloid GPLVM for Discovering Continuous Hierarchies via Nonparametric Estimation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Koshi Watanabe
Keisuke Maeda
Takahiro Ogawa
Miki Haseyama
844
0
0
22 Oct 2024
Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines
Neural Information Processing Systems (NeurIPS), 2024
Edward Milsom
Ben Anson
Laurence Aitchison
218
0
0
08 Oct 2024
Physics-Informed Variational State-Space Gaussian Processes
Neural Information Processing Systems (NeurIPS), 2024
Oliver Hamelijnck
Arno Solin
Theodoros Damoulas
295
6
0
20 Sep 2024
Amortized Variational Inference for Deep Gaussian Processes
Qiuxian Meng
Yongyou Zhang
195
0
0
18 Sep 2024
Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling
Jian Xu
Shian Du
Junmei Yang
Qianli Ma
Delu Zeng
BDL
507
0
0
13 Aug 2024
Fully Bayesian Differential Gaussian Processes through Stochastic Differential Equations
Jian Xu
Zhiqi Lin
Min Chen
Junmei Yang
Delu Zeng
John Paisley
430
0
0
12 Aug 2024
Flexible Bayesian Last Layer Models Using Implicit Priors and Diffusion Posterior Sampling
Jian Xu
Zhiqi Lin
Shigui Li
Min Chen
Junmei Yang
Delu Zeng
John Paisley
BDL
326
0
0
07 Aug 2024
Monotonic warpings for additive and deep Gaussian processes
Statistics and computing (Stat. Comput.), 2024
Chang Liu
Lauren J. Beesley
Annie S. Booth
Robert B. Gramacy
Yan Zhao
218
5
0
02 Aug 2024
Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference
Jian Xu
Delu Zeng
John Paisley
DiffM
260
11
0
24 Jul 2024
Scalable Multi-Output Gaussian Processes with Stochastic Variational Inference
Xiaoyu Jiang
Sokratia Georgaka
Magnus Rattray
Mauricio A. Alvarez
226
0
0
02 Jul 2024
Adaptive RKHS Fourier Features for Compositional Gaussian Process Models
Xinxing Shi
Thomas Baldwin-McDonald
Mauricio A. Álvarez
418
0
0
01 Jul 2024
Latent Variable Double Gaussian Process Model for Decoding Complex Neural Data
Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2024
Navid Ziaei
Joshua J. Stim
Melanie D. Goodman-Keiser
S. Sponheim
A. Widge
Sasoun Krikorian
Ali Yousefi
109
2
0
08 May 2024
Multi-fidelity Gaussian process surrogate modeling for regression problems in physics
Kislaya Ravi
Vladyslav Fediukov
Felix Dietrich
T. Neckel
Fabian Buse
Michael Bergmann
H. Bungartz
AI4CE
222
12
0
18 Apr 2024
Universal Functional Regression with Neural Operator Flows
Yaozhong Shi
Angela F. Gao
Zachary E. Ross
Kamyar Azizzadenesheli
263
6
0
03 Apr 2024
On Uncertainty Quantification for Near-Bayes Optimal Algorithms
Ziyu Wang
Chris Holmes
UQCV
317
3
0
28 Mar 2024
Deep Horseshoe Gaussian Processes
Ismael Castillo
Thibault Randrianarisoa
BDL
UQCV
329
7
0
04 Mar 2024
Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling
Ruijia Niu
D. Wu
Kai Kim
Yi-An Ma
D. Watson‐Parris
Rose Yu
AI4CE
290
10
0
29 Feb 2024
Stopping Bayesian Optimization with Probabilistic Regret Bounds
James T. Wilson
225
12
0
26 Feb 2024
Gradient-enhanced deep Gaussian processes for multifidelity modelling
Viv Bone
Chris van der Heide
Kieran Mackle
Ingo Jahn
P. Dower
Chris Manzie
182
2
0
25 Feb 2024
Multi-Fidelity Methods for Optimization: A Survey
Ke Li
Fan Li
AI4CE
241
16
0
15 Feb 2024
Flexible Infinite-Width Graph Convolutional Neural Networks
Ben Anson
Edward Milsom
Laurence Aitchison
SSL
GNN
211
1
0
09 Feb 2024
Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes
Yingyi Chen
Qinghua Tao
F. Tonin
Johan A. K. Suykens
249
1
0
02 Feb 2024
A Bayesian Gaussian Process-Based Latent Discriminative Generative Decoder (LDGD) Model for High-Dimensional Data
Navid Ziaei
Behzad Nazari
Uri T. Eden
A. Widge
Ali Yousefi
304
4
0
29 Jan 2024
Sparse Variational Student-t Processes
AAAI Conference on Artificial Intelligence (AAAI), 2023
Jian Xu
Delu Zeng
343
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
338
1
0
24 Nov 2023
Deep Transformed Gaussian Processes
Francisco Javier Sáez-Maldonado
Juan Maroñas
Daniel Hernández-Lobato
342
0
0
27 Oct 2023
Thin and Deep Gaussian Processes
Neural Information Processing Systems (NeurIPS), 2023
Daniel Augusto R. M. A. de Souza
Alexander Nikitin
S. T. John
Magnus Ross
Mauricio A. Alvarez
M. Deisenroth
Joao P. P. Gomes
Diego Mesquita
C. L. C. Mattos
186
5
0
17 Oct 2023
On permutation symmetries in Bayesian neural network posteriors: a variational perspective
Neural Information Processing Systems (NeurIPS), 2023
Simone Rossi
Ankit Singh
T. Hannagan
238
3
0
16 Oct 2023
Safe Exploration in Reinforcement Learning: A Generalized Formulation and Algorithms
Neural Information Processing Systems (NeurIPS), 2023
Akifumi Wachi
Wataru Hashimoto
Xun Shen
Kazumune Hashimoto
269
20
0
05 Oct 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
Sampling-Free Probabilistic Deep State-Space Models
Andreas Look
M. Kandemir
Barbara Rakitsch
Jan Peters
239
2
0
15 Sep 2023
To Predict or to Reject: Causal Effect Estimation with Uncertainty on Networked Data
Industrial Conference on Data Mining (IDM), 2023
Hechuan Wen
Tong Chen
Li Kheng Chai
S. Sadiq
Kai Zheng
Hongzhi Yin
CML
208
2
0
15 Sep 2023
Out of Distribution Detection via Domain-Informed Gaussian Process State Space Models
IEEE Conference on Decision and Control (CDC), 2023
Alonso Marco
Elias Morley
Claire Tomlin
330
6
0
13 Sep 2023
On the meaning of uncertainty for ethical AI: philosophy and practice
Cassandra Bird
Daniel Williamson
Sabina Leonelli
169
1
0
11 Sep 2023
Exploring the Efficacy of Statistical and Deep Learning Methods for Large Spatial Datasets: A Case Study
Journal of Agricultural Biological and Environmental Statistics (JABES), 2023
A. Hazra
Pratik Nag
Rishikesh Yadav
Ying Sun
213
6
0
10 Aug 2023
1
2
3
4
5
Next
Page 1 of 5
