From the 1 of 4 linked papers with an AI index.
4 papers
ANGLE: Angular Neural Generative Learning via Engression
Rajdeep Pathak, Archi Roy, Tanujit Chakraborty
The paper introduces ANGLE, a lightweight deep generative model that learns the full conditional distribution of circular (angular) data given various covariates, enabling better p…
Deep Generative Spatiotemporal Engression for Probabilistic Forecasting of Epidemics
Rajdeep Pathak, Tanujit Chakraborty
Accurate and reliable forecasting of epidemic incidences is critical for public health preparedness, yet it remains a challenging task due to complex nonlinear temporal dependencie…
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…
Quantifying Membership Disclosure Risk for Tabular Synthetic Data Using Kernel Density Estimators
Rajdeep Pathak, Sayantee Jana, Amit Basak
The use of synthetic data has become increasingly popular as a privacy-preserving alternative to sharing real datasets, especially in sensitive domains such as healthcare, finance,…