This work introduces a novel probabilistic deep learning technique calle...
Hawkes processes have recently risen to the forefront of tools when it c...
Online learning of Hawkes processes has received increasing attention in...
Hawkes processes have recently gained increasing attention from the mach...
Geostationary satellite (GOES) imagery provides a high temporal resoluti...
Many popular algorithmic fairness measures depend on the joint distribut...
Many areas of science make extensive use of computer simulators that
imp...
Conditional density models f(y|x), where x represents a potentially
high...
Climate models play a crucial role in understanding the effect of
enviro...
Tropical cyclone (TC) intensity forecasts are ultimately issued by human...
This paper introduces an approach to architectural “distant reading”: th...
Machine learning-based Risk Assessment Instruments are increasingly wide...
Estimates of the Hubble constant, $H_0$, from the local distance ladder ...
We propose Lebesgue Regression, a non-parametric high-dimensional regres...
Entity resolution or record linkage is the task of identifying records r...
Wildfires are rare catastrophic events that are influenced by global cli...
Parameter estimation, statistical tests and confidence sets are the
corn...
It is well known in astronomy that propagating non-Gaussian prediction
u...
Hurricanes and, more generally, tropical cyclones (TCs) are rare, comple...
Complex phenomena are often modeled with computationally intensive
feed-...