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Deep echo state networks with uncertainty quantification for spatio‐temporal forecasting

https://doi.org/10.1002/env.2553
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/asmb.2399openalex-snapshot
Deep learning for spatio‐temporal modeling: Dynamic traffic flows and high frequency trading
inferredcites →https://doi.org/10.1002/env.2266openalex-snapshot
Physically motivated scale interaction parameterization in reduced rank quadratic nonlinear dynamic spatio‐temporal models
inferredcites →https://doi.org/10.1002/env.2374openalex-snapshot
A model‐based approach for analog spatio‐temporal dynamic forecasting
inferredcites →https://doi.org/10.1002/env.2456openalex-snapshot
Sparsity in nonlinear dynamic spatiotemporal models using implied advection
inferredcites →https://doi.org/10.1002/qj.2521openalex-snapshot
Log‐normal distribution based Ensemble Model Output Statistics models for probabilistic wind‐speed forecasting
inferredcites →https://doi.org/10.1002/qj.2559openalex-snapshot
Trends in the skill of weather prediction at lead times of 1–14 days
inferredcites →https://doi.org/10.1002/sta4.160openalex-snapshot
An ensemble quadratic echo state network for non‐linear spatio‐temporal forecasting
inferredcites →https://doi.org/10.1002/wics.1341openalex-snapshot
Modern perspectives on statistics for spatio‐temporal data
inferredcites →https://doi.org/10.1007/978-3-319-23525-7_22openalex-snapshot
Sparse Bayesian Recurrent Neural Networks
inferredcites →https://doi.org/10.1007/978-3-642-35289-8_36openalex-snapshot
A Practical Guide to Applying Echo State Networks
inferredcites →https://doi.org/10.1007/bfb0091924openalex-snapshot
Detecting strange attractors in turbulence
inferredcites →https://doi.org/10.1007/s11749-010-0209-zopenalex-snapshot
A general science-based framework for dynamical spatio-temporal models
inferredcites →https://doi.org/10.1016/j.cosrev.2009.03.005openalex-snapshot
Reservoir computing approaches to recurrent neural network training
inferredcites →https://doi.org/10.1016/j.jcp.2004.04.013openalex-snapshot
A computational strategy for multiscale systems with applications to Lorenz 96 model
inferredcites →https://doi.org/10.1016/j.neunet.2016.09.009openalex-snapshot
Echo State Networks for data-driven downhole pressure estimation in gas-lift oil wells
inferredcites →https://doi.org/10.1017/cbo9780511617652.004openalex-snapshot
Predictability – a problem partly solved
inferredcites →https://doi.org/10.1017/s1350482701002092openalex-snapshot
A skill score based on economic value for probability forecasts
inferredcites →https://doi.org/10.1029/2002jd003114openalex-snapshot
Performance and analysis of the constructed analogue method applied to U.S. soil moisture over 1981–2001
inferredcites →https://doi.org/10.1029/2003jd004345openalex-snapshot
Climate Prediction Center global monthly soil moisture data set at 0.5° resolution for 1948 to present
inferredcites →https://doi.org/10.1029/2004jd005182openalex-snapshot
A simulated soil moisture based drought analysis for the United States
inferredcites →https://doi.org/10.1073/pnas.1512080112openalex-snapshot
Discrete approach to stochastic parametrization and dimension reduction in nonlinear dynamics
inferredcites →https://doi.org/10.1073/pnas.79.8.2554openalex-snapshot
Neural networks and physical systems with emergent collective computational abilities.
inferredcites →https://doi.org/10.1088/0951-7715/29/9/2888openalex-snapshot
Analog forecasting with dynamics-adapted kernels
inferredcites →https://doi.org/10.1109/tasl.2013.2280209openalex-snapshot
Acoustic Modeling With Hierarchical Reservoirs
inferredcites →https://doi.org/10.1109/tnnls.2012.2188414openalex-snapshot
Chaotic Time Series Prediction Based on a Novel Robust Echo State Network
inferredcites →https://doi.org/10.1109/tnnls.2013.2250299openalex-snapshot
Prediction Intervals for a Noisy Nonlinear Time Series Based on a Bootstrapping Reservoir Computing Network Ensemble
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1146/annurev-statistics-062713-085831openalex-snapshot
Probabilistic Forecasting
inferredcites →https://doi.org/10.1175/1520-0434(1994)009<0078:afotso>2.0.co;2openalex-snapshot
Analog (Nonlinear) Forecasts of the Southern Oscillation Index Time Series
inferredcites →https://doi.org/10.1175/1520-0434(1997)012<0633:aenoso>2.0.co;2openalex-snapshot
An El Niño–Southern Oscillation Climatology and Persistence (CLIPER) Forecasting Scheme
inferredcites →https://doi.org/10.1175/1520-0442(1993)006<1067:ponsst>2.0.co;2openalex-snapshot
Prediction of Niño 3 Sea Surface Temperatures Using Linear Inverse Modeling
inferredcites →https://doi.org/10.1175/1520-0442(1998)011<0029:feeann>2.0.co;2openalex-snapshot
Forecasting ENSO Events: A Neural Network–Extended EOF Approach
inferredcites →https://doi.org/10.1175/1520-0442(2000)013<0287:scbnna>2.0.co;2openalex-snapshot
Skill Comparisons between Neural Networks and Canonical Correlation Analysis in Predicting the Equatorial Pacific Sea Surface Temperatures
inferredcites →https://doi.org/10.1175/1520-0442(2001)013<3953:llpops>2.0.co;2openalex-snapshot
Long-Lead Prediction of Pacific SSTs via Bayesian Dynamic Modeling
inferredcites →https://doi.org/10.1175/1520-0469(1963)020<0130:dnf>2.0.co;2openalex-snapshot
Deterministic Nonperiodic Flow
inferredcites →https://doi.org/10.1175/1520-0477(1999)080<0217:psosad>2.0.co;2openalex-snapshot
Predictive Skill of Statistical and Dynamical Climate Models in SST Forecasts during the 1997—98 El Niño Episode and the 1998 La Niña Onset
inferredcites →https://doi.org/10.1175/1520-0485(2001)031<1579:edsmoe>2.0.co;2openalex-snapshot
Empirical Dynamical System Modeling of ENSO Using Nonlinear Inverse Techniques
inferredcites →https://doi.org/10.1175/2007jcli1578.1openalex-snapshot
Synoptic Circulation and Land Surface Influences on Convection in the Midwest U.S. “Corn Belt” during the Summers of 1999 and 2000. Part I: Composite Synoptic Environments
inferredcites →https://doi.org/10.1175/2007jcli2100.1openalex-snapshot
Improvements to NOAA’s Historical Merged Land–Ocean Surface Temperature Analysis (1880–2006)
inferredcites →https://doi.org/10.1175/2008jas2566.1openalex-snapshot
Subgrid-Scale Parameterization with Conditional Markov Chains
inferredcites →https://doi.org/10.1175/jcli3420.1openalex-snapshot
Did the ECMWF Seasonal Forecast Model Outperform Statistical ENSO Forecast Models over the Last 15 Years?
inferredcites →https://doi.org/10.1175/jcli3544.1openalex-snapshot
Multilevel Regression Modeling of Nonlinear Processes: Derivation and Applications to Climatic Variability
inferredcites →https://doi.org/10.1175/jcli3567.1openalex-snapshot
A Hierarchy of Data-Based ENSO Models
inferredcites →https://doi.org/10.1175/jcli4288.1openalex-snapshot
Soil Moisture–Atmosphere Interactions during the 2003 European Summer Heat Wave
inferredcites →https://doi.org/10.1175/mwr2904.1openalex-snapshot
Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation
inferredcites →https://doi.org/10.1198/jasa.2009.tm09036openalex-snapshot
Statistical Agent-Based Models for Discrete Spatio-Temporal Systems
inferredcites →https://doi.org/10.1214/07-aihp148openalex-snapshot
Validity of the parametric bootstrap for goodness-of-fit testing in semiparametric models
inferredcites →https://doi.org/10.1214/ss/1177011136openalex-snapshot
Inference from Iterative Simulation Using Multiple Sequences
inferredcites →https://doi.org/10.1256/qj.04.03openalex-snapshot
Effects of stochastic parametrizations in the Lorenz '96 system
inferredcites →https://doi.org/10.2134/jpa1989.0103openalex-snapshot
Correlations between Soil Nitrate Concentrations in Late Spring and Corn Yields in Iowa
inferredcites →https://doi.org/10.3390/e21020184openalex-snapshot
Bayesian Recurrent Neural Network Models for Forecasting and Quantifying Uncertainty in Spatial-Temporal Data
inferredcites →https://doi.org/10.4249/scholarpedia.2330openalex-snapshot
Echo state network
inferredcites →https://doi.org/10.48550/arxiv.1711.05255openalex-snapshot
Deep-ESN: A Multiple Projection-encoding Hierarchical Reservoir Computing Framework
inferredcites →https://doi.org/10.5194/npg-22-601-2015openalex-snapshot
A framework for variational data assimilation with superparameterization
inferredcites →https://doi.org/10.7551/mitpress/1120.003.0080openalex-snapshot
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering

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Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/env.2628openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/env.2833openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/env.70030openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/env.70119openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/jae.2959openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/sam.11706openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-19-6142-7_37openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s13163-020-00359-7openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s13253-019-00361-7openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s13253-025-00696-4openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s40815-023-01544-8openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s41745-022-00298-wopenalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.asoc.2022.108526openalex-snapshot
Randomization-based machine learning in renewable energy prediction problems: Critical literature review, new results and perspectives
inferred← citeshttps://doi.org/10.1016/j.asoc.2022.109454openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.atech.2025.101123openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.geodrs.2021.e00359openalex-snapshot
Digital soil mapping and assessment for Australia and beyond: A propitious future
inferred← citeshttps://doi.org/10.1016/j.heliyon.2024.e24188openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.inffus.2021.05.008openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jcp.2021.110412openalex-snapshot
A data-driven, physics-informed framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings
inferred← citeshttps://doi.org/10.1016/j.mlwa.2023.100456openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.petrol.2021.109068openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.spasta.2020.100408openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.spasta.2023.100732openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.spasta.2024.100813openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.spasta.2024.100827openalex-snapshot
Echo state network-enhanced symbolic regression for spatio-temporal binary stochastic cellular automata
inferred← citeshttps://doi.org/10.1029/2020ms002084openalex-snapshot
Data‐Driven Super‐Parameterization Using Deep Learning: Experimentation With Multiscale Lorenz 96 Systems and Transfer Learning
inferred← citeshttps://doi.org/10.1029/2024jh000291openalex-snapshot
Forecasting High Resolution Precipitation Events With Logistic Echo State Networks
inferred← citeshttps://doi.org/10.1029/2024ms004779openalex-snapshot
Data‐Driven Dynamic Modal Bias Analysis and Correction for Earth System Models
inferred← citeshttps://doi.org/10.1038/s41598-019-49242-6openalex-snapshot
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inferred← citeshttps://doi.org/10.1063/5.0077302openalex-snapshot
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inferred← citeshttps://doi.org/10.1063/5.0186854openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/00401706.2021.1921035openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/00949655.2021.1925279openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/01621459.2021.1887741openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/01621459.2024.2422131openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/01621459.2026.2632865openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/10618600.2026.2670661openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/26941899.2025.2554883openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/26941899.2025.2565243openalex-snapshot
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inferred← citeshttps://doi.org/10.1088/2632-2153/adc53bopenalex-snapshot
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inferred← citeshttps://doi.org/10.1093/biomtc/ujae057openalex-snapshot
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inferred← citeshttps://doi.org/10.1093/jrsssa/qnad033openalex-snapshot
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inferred← citeshttps://doi.org/10.1093/jrsssb/qkae118openalex-snapshot
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inferred← citeshttps://doi.org/10.1093/jrsssc/qlaf007openalex-snapshot
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inferred← citeshttps://doi.org/10.1103/physreve.108.064209openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/access.2023.3343467openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/isncc58260.2023.10323907openalex-snapshot
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inferred← citeshttps://doi.org/10.1111/ele.13462openalex-snapshot
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inferred← citeshttps://doi.org/10.1111/rssc.12540openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3447548.3467449openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3512290.3528721openalex-snapshot
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inferred← citeshttps://doi.org/10.1146/annurev-statistics-033021-112628openalex-snapshot
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inferred← citeshttps://doi.org/10.1175/jcli-d-19-0769.1openalex-snapshot
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inferred← citeshttps://doi.org/10.1214/22-aoas1683openalex-snapshot
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inferred← citeshttps://doi.org/10.1360/ssi-2019-0183openalex-snapshot
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inferred← citeshttps://doi.org/10.21203/rs.3.rs-9210324/v1openalex-snapshot
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inferred← citeshttps://doi.org/10.2139/ssrn.3572181openalex-snapshot
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inferred← citeshttps://doi.org/10.2166/hydro.2023.035openalex-snapshot
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inferred← citeshttps://doi.org/10.2172/1769729openalex-snapshot
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inferred← citeshttps://doi.org/10.22541/au.171901001.17451463/v1openalex-snapshot
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inferred← citeshttps://doi.org/10.2514/1.j066257openalex-snapshot
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inferred← citeshttps://doi.org/10.31223/osf.io/fbxnsopenalex-snapshot
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inferred← citeshttps://doi.org/10.32469/10355/86508openalex-snapshot
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inferred← citeshttps://doi.org/10.32469/10355/96967openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/frai.2024.1410841openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/cli12110189openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/e26080634openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/en13092390openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/info16100917openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/math11061503openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/math8081374openalex-snapshot
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inferred← citeshttps://doi.org/10.48550/arxiv.1909.00076openalex-snapshot
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inferred← citeshttps://doi.org/10.48550/arxiv.2002.11815openalex-snapshot
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inferred← citeshttps://doi.org/10.5194/acp-20-2303-2020openalex-snapshot
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inferred← citeshttps://doi.org/10.5194/gmd-18-1041-2025openalex-snapshot
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inferred← citeshttps://doi.org/10.5194/npg-27-373-2020openalex-snapshot
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