The neural hawkes process: A neurally self-modulating multivariate point process
Many events occur in the world. Some event types are stochastically excited or inhibited—in
the sense of having their probabilities elevated or decreased—by patterns in the sequence …
the sense of having their probabilities elevated or decreased—by patterns in the sequence …
Self-attentive Hawkes process
Capturing the occurrence dynamics is crucial to predicting which type of events will happen
next and when. A common method to do this is through Hawkes processes. To enhance …
next and when. A common method to do this is through Hawkes processes. To enhance …
Language models can improve event prediction by few-shot abductive reasoning
Large language models have shown astonishing performance on a wide range of reasoning
tasks. In this paper, we investigate whether they could reason about real-world events and …
tasks. In this paper, we investigate whether they could reason about real-world events and …
Blind wireless network topology inference
This work proposes a framework to discover the topology of a non-collaborative packet-
based wireless network using radio-frequency (RF) sensors. The methodology developed is …
based wireless network using radio-frequency (RF) sensors. The methodology developed is …
Learning hawkes processes from a handful of events
F Salehi, W Trouleau… - Advances in neural …, 2019 - proceedings.neurips.cc
Learning the causal-interaction network of multivariate Hawkes processes is a useful task in
many applications. Maximum-likelihood estimation is the most common approach to solve …
many applications. Maximum-likelihood estimation is the most common approach to solve …
The multivariate Hawkes process in high dimensions: Beyond mutual excitation
The Hawkes process is a class of point processes whose future depends on their own
history. Previous theoretical work on the Hawkes process is limited to a special case in …
history. Previous theoretical work on the Hawkes process is limited to a special case in …