Deep Echo State Networks with Uncertainty Quantification for Spatio-Temporal Forecasting

28 June 2018

Papers citing "Deep Echo State Networks with Uncertainty Quantification for Spatio-Temporal Forecasting"

21 / 21 papers shown

Title
A Physics-Informed Convolutional Long Short Term Memory Statistical Model for Fluid Thermodynamics Simulations Luca Menicali Andrew Grace David H. Richter Stefano Castruccio AI4CE 24 0 0 16 May 2025
Hierarchical Count Echo State Network Models with Application to Graduate Student Enrollments Qi Wang Paul A. Parker Robert B. Lund 61 0 0 24 Jan 2025
Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events Ayush Khot Xihaier Luo Ai Kagawa Shinjae Yoo EDL BDL 81 0 0 18 Dec 2024
CESAR: A Convolutional Echo State AutoencodeR for High-Resolution Wind Forecasting Matthew Bonas Paolo Giani Paola Crippa Stefano Castruccio 73 0 0 13 Dec 2024
Modeling High-Resolution Spatio-Temporal Wind with Deep Echo State Networks and Stochastic Partial Differential Equations Kesen Wang Minwoo Kim S. Castruccio M. Genton 70 0 0 10 Dec 2024
Echo State Networks for Spatio-Temporal Area-Level Data Zhenhua Wang S. Holan C. Wikle 29 2 0 14 Oct 2024
Probabilistic load forecasting with Reservoir Computing Michele Guerra Simone Scardapane F. Bianchi BDL 21 3 0 24 Aug 2023
Variability of echo state network prediction horizon for partially observed dynamical systems Ajit Mahata Reetish Padhi A. Apte 26 1 0 19 Jun 2023
REDS: Random Ensemble Deep Spatial prediction Ranadeep Daw C. Wikle 23 10 0 09 Nov 2022
Data-driven and machine-learning based prediction of wave propagation behavior in dam-break flood Changli Li Zheng Han Yan-ge Li Ming Li Wei-dong Wang 16 2 0 19 Sep 2022
Survey on Deep Fuzzy Systems in regression applications: a view on interpretability Jorge S. S. Júnior Jérôme Mendes F. Souza C. Premebida AI4CE 23 9 0 09 Sep 2022
Hyperparameter Tuning in Echo State Networks Filip Matzner 30 2 0 16 Jul 2022
Statistical Deep Learning for Spatial and Spatio-Temporal Data C. Wikle A. Zammit‐Mangion BDL 29 45 0 05 Jun 2022
PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics Arka Daw M. Maruf Anuj Karpatne AI4CE 10 42 0 06 Jun 2021
Randomization-based Machine Learning in Renewable Energy Prediction Problems: Critical Literature Review, New Results and Perspectives Javier Del Ser D. Casillas-Pérez L. Cornejo-Bueno Luis Prieto-Godino J. Sanz-Justo C. Casanova-Mateo S. Salcedo-Sanz AI4CE 42 42 0 26 Mar 2021
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Li Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 56 1,883 0 12 Nov 2020
Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices Nadja Klein M. Smith David J. Nott BDL AI4TS 24 25 0 05 Oct 2020
A General Bayesian Model for Heteroskedastic Data with Fully Conjugate Full-Conditional Distributions Paul A. Parker S. Holan S. Wills 11 12 0 28 Sep 2020
Uncertainty Quantification for Sparse Deep Learning Yuexi Wang Veronika Rockova BDL UQCV 36 31 0 26 Feb 2020
Deep Integro-Difference Equation Models for Spatio-Temporal Forecasting A. Zammit‐Mangion C. Wikle 15 47 0 29 Oct 2019
Data-driven prediction of a multi-scale Lorenz 96 chaotic system using deep learning methods: Reservoir computing, ANN, and RNN-LSTM Ashesh Chattopadhyay Pedram Hassanzadeh D. Subramanian AI4CE 19 40 0 20 Jun 2019