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Deep Sigma Point Processes
v1v2 (latest)

Deep Sigma Point Processes

Conference on Uncertainty in Artificial Intelligence (UAI), 2020
21 February 2020
M. Jankowiak
Geoff Pleiss
Jacob R. Gardner
    BDL
ArXiv (abs)PDFHTML

Papers citing "Deep Sigma Point Processes"

15 / 15 papers shown
Deep Gaussian Process Proximal Policy Optimization
Deep Gaussian Process Proximal Policy Optimization
Matthijs van der Lende
Juan Cardenas-Cartagena
GPBDLUQCV
411
0
0
22 Nov 2025
A Physics-Guided Probabilistic Surrogate Modeling Framework for Digital Twins of Underwater Radiated Noise
A Physics-Guided Probabilistic Surrogate Modeling Framework for Digital Twins of Underwater Radiated Noise
Indu Kant Deo
Akash Venkateshwaran
R. Jaiman
AI4CE
92
0
0
30 Sep 2025
Evaluating Uncertainty in Deep Gaussian Processes
Evaluating Uncertainty in Deep Gaussian Processes
Matthijs van der Lende
Jeremias Lino Ferrao
Niclas Müller-Hof
UQCV
284
1
0
24 Apr 2025
Stochastic Process Learning via Operator Flow Matching
Stochastic Process Learning via Operator Flow Matching
Yaozhong Shi
Zachary E. Ross
D. Asimaki
Kamyar Azizzadenesheli
630
7
0
07 Jan 2025
Deep Q-Exponential Processes
Deep Q-Exponential ProcessesSymposium on Advances in Approximate Bayesian Inference (AABI), 2024
Zhi Chang
Chukwudi Obite
Shuang Zhou
Shiwei Lan
BDL
273
0
0
29 Oct 2024
Amortized Variational Inference for Deep Gaussian Processes
Amortized Variational Inference for Deep Gaussian Processes
Qiuxian Meng
Yongyou Zhang
202
1
0
18 Sep 2024
Universal Functional Regression with Neural Operator Flows
Universal Functional Regression with Neural Operator Flows
Yaozhong Shi
Angela F. Gao
Zachary E. Ross
Kamyar Azizzadenesheli
322
6
0
03 Apr 2024
Gradient-enhanced deep Gaussian processes for multifidelity modelling
Gradient-enhanced deep Gaussian processes for multifidelity modelling
Viv Bone
Chris van der Heide
Kieran Mackle
Ingo Jahn
P. Dower
Chris Manzie
216
3
0
25 Feb 2024
Gaussian Process Latent Variable Modeling for Few-shot Time Series Forecasting
Gaussian Process Latent Variable Modeling for Few-shot Time Series ForecastingIEEE Transactions on Knowledge and Data Engineering (TKDE), 2022
Yunyao Cheng
Chenjuan Guo
Kai Chen
Kai Zhao
B. Yang
Jiandong Xie
Christian S. Jensen
Feiteng Huang
Kai Zheng
AI4TS
335
1
0
20 Dec 2022
Photoelectric Factor Prediction Using Automated Learning and Uncertainty
  Quantification
Photoelectric Factor Prediction Using Automated Learning and Uncertainty Quantification
K. Alsamadony
A. Ibrahim
S. Elkatatny
A. Abdulraheem
131
2
0
17 Jun 2022
Bayesian Meta-Learning Through Variational Gaussian Processes
Bayesian Meta-Learning Through Variational Gaussian Processes
Vivek Myers
Nikhil Sardana
BDLUQCV
183
7
0
21 Oct 2021
Scalable Cross Validation Losses for Gaussian Process Models
Scalable Cross Validation Losses for Gaussian Process Models
M. Jankowiak
Geoff Pleiss
204
6
0
24 May 2021
Uncertainty-aware Remaining Useful Life predictor
Uncertainty-aware Remaining Useful Life predictor
Luca Biggio
Alexander Wieland
M. A. Chao
I. Kastanis
Olga Fink
AI4CE
195
8
0
08 Apr 2021
Fast Deep Mixtures of Gaussian Process Experts
Fast Deep Mixtures of Gaussian Process ExpertsMachine-mediated learning (ML), 2020
Clement Etienam
K. Law
S. Wade
Vitaly Zankin
352
4
0
11 Jun 2020
Direct loss minimization algorithms for sparse Gaussian processes
Direct loss minimization algorithms for sparse Gaussian processesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Yadi Wei
Rishit Sheth
Roni Khardon
316
14
0
07 Apr 2020
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