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cs.LG2026
NeuroMem-FHP: A Likelihood-Free Deep Learning Framework for Parameter Estimation of Fractional Hawkes Process
Neha Gupta, Aditya Maheshwari
In this paper, we propose deep learning based NeuroMem-FHP framework for estimating the parameters of the fractional Hawkes process (FHP), a self-exciting point process that captur…
cs.LG2026
NEXUS: A compact neural architecture for high-resolution spatiotemporal air quality forecasting in Delhi National Capital Region
Rampunit Kumar, Aditya Maheshwari
Urban air pollution in megacities poses critical public health challenges, particularly in Delhi National Capital Region (NCR) where severe degradation affects millions. We present…
cs.LG2025
NeuroMemFPP: A recurrent neural approach for memory-aware parameter estimation in fractional Poisson process
Neha Gupta, Aditya Maheshwari
In this paper, we propose a recurrent neural network (RNN)-based framework for estimating the parameters of the fractional Poisson process (FPP), which models event arrivals with m…