Deep Integro-Difference Equation Models for Spatio-Temporal Forecasting

29 October 2019

Papers citing "Deep Integro-Difference Equation Models for Spatio-Temporal Forecasting"

10 / 10 papers shown

Title
Fast Likelihood-Free Parameter Estimation for Lévy Processes Nicolas Coloma William Kleiber 103 0 0 03 May 2025
Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks Matthew Sainsbury-Dale A. Zammit‐Mangion J. Richards Raphael Huser 409 15 0 04 Oct 2023
Deep Compositional Spatial Models A. Zammit‐Mangion T. L. J. Ng Quan Vu Maurizio Filippone 74 56 0 06 Jun 2019
Comparison of Deep Neural Networks and Deep Hierarchical Models for Spatio-Temporal Data C. Wikle BDL 75 19 0 22 Feb 2019
Deep Echo State Networks with Uncertainty Quantification for Spatio-Temporal Forecasting Patrick L. McDermott C. Wikle BDL 63 79 0 28 Jun 2018
Bayesian Deep Net GLM and GLMM Minh-Ngoc Tran Nghia Nguyen David J. Nott Robert Kohn BDL 82 75 0 25 May 2018
Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge Emmanuel de Bézenac Arthur Pajot Patrick Gallinari PINN AI4CE 83 318 0 21 Nov 2017
An Ensemble Quadratic Echo State Network for Nonlinear Spatio-Temporal Forecasting Patrick L. McDermott C. Wikle 49 72 0 16 Aug 2017
Ensemble Kalman methods for high-dimensional hierarchical dynamic space-time models Matthias Katzfuss Jonathan R. Stroud C. Wikle 66 68 0 23 Apr 2017
FlowNet: Learning Optical Flow with Convolutional Networks Philipp Fischer Alexey Dosovitskiy Eddy Ilg Philip Häusser C. Hazirbas Vladimir Golkov Patrick van der Smagt Daniel Cremers Thomas Brox 3DPC 282 4,169 0 26 Apr 2015