Decentralized and incomplete data sources are prevalent in real-world
ap...
We propose a new causal inference framework to learn causal effects from...
We present a new and straightforward algorithm that simulates exact samp...
Many modern applications collect data that comes in federated spirit, wi...
The literature for count modeling provides useful tools to conduct causa...
Uncertainty quantification has been a core of the statistical machine
le...
We propose a simulation method for multidimensional Hawkes processes bas...
We present the first framework for Gaussian-process-modulated Poisson
pr...
This chapter provides an accessible introduction for point processes, an...
We propose an extension to Hawkes processes by treating the levels of
se...