From the 1 of 9 linked papers with an AI index.
9 papers
TREA-Net: A Transferable Residual Epidemiological Adaptation Network for Dengue Incidence Forecasting
Inesh Shukla, Madhurima Panja, Tanujit Chakraborty +1
The paper introduces TREA-Net, a lightweight neural network that adapts pretrained time‑series models to forecast dengue incidence in regions with limited surveillance data by inco…
GraphSVR: A Graph Convolutional Support Vector Regression Framework for Robust Spatiotemporal Air Pollution Forecasting
Nourin Jahan, Muhammed Navas T, Tanujit Chakraborty +1
Urban air quality forecasting is challenging because pollutant concentrations are nonlinear, nonstationary, spatiotemporally dependent, and often affected by anomalous observations…
Deep Generative Transformers for Probabilistic Time Series and Spatiotemporal Forecasting
Rajdeep Pathak, Rahul Goswami, Madhurima Panja +2
Reliable uncertainty quantification is paramount for forecasting multivariate time series and spatiotemporal data. While Transformer architectures excel at sequence modeling, curre…
Neural ARFIMA model for forecasting BRIC exchange rates with long memory
Donia Besher, Madhurima Panja, Shovon Sengupta +1
Exchange rate forecasting remains a challenging problem, particularly for emerging economies, where the observed time series exhibit pronounced long-memory dependence, nonlinear dy…
EpiCastBench: Datasets and Benchmarks for Multivariate Epidemic Forecasting
Madhurima Panja, Danny D'Agostino, Huitao Li +2
The increasing adoption of data-driven decision-making in public health has established epidemic forecasting as a critical area of research. Recent advances in multivariate forecas…
Turning Time Series into Algebraic Equations: Symbolic Machine Learning for Interpretable Modeling of Chaotic Time Series
Madhurima Panja, Grace Younes, Tanujit Chakraborty
Chaotic time series are notoriously difficult to forecast. Small uncertainties in initial conditions amplify rapidly, while strong nonlinearities and regime dependent variability c…