14 citations as recorded by crossref.

1. Evaluation of statistical climate reconstruction methods based on pseudoproxy experiments using linear and machine-learning methods Z. Zhang et al. 10.5194/cp-18-2643-2022
2. Can machine-learning algorithms improve upon classical palaeoenvironmental reconstruction models? P. Sun et al. 10.5194/cp-20-2373-2024
3. pH trends and seasonal cycle in the coastal Balearic Sea reconstructed through machine learning S. Flecha et al. 10.1038/s41598-022-17253-5
4. Loss of Earth system resilience during early Eocene transient global warming events S. Setty et al. 10.1126/sciadv.ade5466
5. Deep Learning-Based Time Series Analysis for Environment Changes A. Anand et al. 10.54105/ijainn.B3904.04061024
6. Estimating prediction horizon of reservoir computer on L63 system when observed variables are incomplete Y. Huang & Z. Fu 10.1088/2632-072X/acd21c
7. A new method of nonlinear causality detection: Reservoir computing Granger causality M. Wang & Z. Fu 10.1016/j.chaos.2021.111675
8. Seasonal prediction of Indian summer monsoon onset with echo state networks T. Mitsui & N. Boers 10.1088/1748-9326/ac0acb
9. Detection of amylase activity and moisture content in rice by reflectance spectroscopy combined with spectral data transformation S. Weng et al. 10.1016/j.saa.2022.122311
10. Dynamical system analysis of a data-driven model constructed by reservoir computing M. Kobayashi et al. 10.1103/PhysRevE.104.044215
11. Seasonal predictions of energy-relevant climate variables through Euro-Atlantic Teleconnections I. Cionni et al. 10.1016/j.cliser.2022.100294
12. Machine learning approach reveals strong link between obliquity amplitude increase and the Mid-Brunhes transition T. Mitsui & N. Boers 10.1016/j.quascirev.2021.107344
13. Lyapunov analysis of data-driven models of high dimensional dynamics using reservoir computing: Lorenz-96 system and fluid flow M. Kobayashi et al. 10.1088/2632-072X/ad5264
14. Detecting causality from time series in a machine learning framework Y. Huang et al. 10.1063/5.0007670