5 citations · 6 across the 5 of their papers we have counts for
5 papers
Turning mechanistic models into forecasters by using machine learning
Amit K. Chakraborty, Hao Wang, Pouria Ramazi
The equations of complex dynamical systems may not be identified by expert knowledge, especially if the underlying mechanisms are unknown. Data-driven discovery methods address thi…
Deep Learning for Disease Outbreak Prediction: A Robust Early Warning Signal for Transcritical Bifurcations
Reza Miry, Amit K. Chakraborty, Russell Greiner +4
Early Warning Signals (EWSs) are vital for implementing preventive measures before a disease turns into a pandemic. While new diseases exhibit unique behaviors, they often share fu…
Dispersion based Recurrent Neural Network Model for Methane Monitoring in Albertan Tailings Ponds
Esha Saha, Oscar Wang, Amit K. Chakraborty +3
Bitumen extraction for the production of synthetic crude oil in Canada's Athabasca Oil Sands industry has recently come under spotlight for being a significant source of greenhouse…
Early detection of disease outbreaks and non-outbreaks using incidence data
Shan Gao, Amit K. Chakraborty, Russell Greiner +2
Forecasting the occurrence and absence of novel disease outbreaks is essential for disease management. Here, we develop a general model, with no real-world training data, that accu…
An early warning indicator trained on stochastic disease-spreading models with different noises
Amit K. Chakraborty, Shan Gao, Reza Miry +4
The timely detection of disease outbreaks through reliable early warning signals (EWSs) is indispensable for effective public health mitigation strategies. Nevertheless, the intric…