PUBLICATIONS AND PREPRINTS

• Deb, S., Sidheekh, S., Clements, C. F., Krishnan, N. C. and Dutta, P. S., Machine learning methods trained on simple models can predict critical transitions in complex natural systems, Royal Society Open Science, The Royal Society Publishing, Vol. 9, 211475(12) (2022). DOI:https://doi.org/10.1098/rsos.211475

•  Deb, S., Bhandary, S., Sinha, S., Jolly, M.K., and Dutta, P.S., Identifying Critical Transitions in Complex Diseases, Journal of Biosciences, Springer, Vol. 47, 25, 1-16 (2022). DOI:https://doi.org/10.1007/s12038-022-00258-7

•   Deb, S., Bhandary, S., and Dutta, P. S., Evading tipping points in socio-mutualistic networks via structure mediated optimal strategy, Journal of Theoretical Biology, Elsevier, Vol. 567, 111494(10) (2023). DOI: https://doi.org/10.1016/j.jtbi.2023.111494

•  4. Bhandary, S., Deb, S. and Dutta, P. S., Rising Temperature Drives Tipping Points in Mutualistic Networks, Royal Society Open Science, The Royal Society Publishing, Vol. 10(2), 221363(17) (2023). DOI: https://doi.org/10.1098/rsos.221363

•  Pal, K., Deb, S. and Dutta, P. S., Tipping points in spatial ecosystems driven by correlated noise, Physical Review E, APS, Vol. 106 (5), 054412 (9) (2022). DOI: https://doi.org/10.1103/PhysRevE.106.054412

• O’Brien,D., Deb, S., Sidheekh, S., Krishnan, N. C. and Dutta, P. S., Clements, C.F., EWSmethods: an R package to forecast tipping points at the community level using early warning signals and machine learning models, (2023). (Under review) DOI:10.22541/au.166801190.00303336/v3

•  Deb, S., and Dutta, P. S., Spatial Mutual information as an indicator of critical transition in spatiotemporal systems, (2023). (To be submitted)