Anticipatory music transformer
We introduce anticipation: a method for constructing a controllable generative model of a
temporal point process (the event process) conditioned asynchronously on realizations of a …
temporal point process (the event process) conditioned asynchronously on realizations of a …
Imputing missing events in continuous-time event streams
Events in the world may be caused by other, unobserved events. We consider sequences of
events in continuous time. Given a probability model of complete sequences, we propose …
events in continuous time. Given a probability model of complete sequences, we propose …
Learning temporal point processes with intermittent observations
V Gupta, S Bedathur… - International …, 2021 - proceedings.mlr.press
Marked temporal point processes (MTPP) have emerged as a powerful framework to model
the underlying generative mechanism of asynchronous events localized in continuous time …
the underlying generative mechanism of asynchronous events localized in continuous time …
Inference for mark-censored temporal point processes
Marked temporal point processes (MTPPs) are a general class of stochastic models for
modeling the evolution of events of different types (“marks”) in continuous time. These …
modeling the evolution of events of different types (“marks”) in continuous time. These …
Learning temporal point processes for efficient retrieval of continuous time event sequences
Recent developments in predictive modeling using marked temporal point processes
(MTPPs) have enabled an accurate characterization of several real-world applications …
(MTPPs) have enabled an accurate characterization of several real-world applications …
Modeling continuous time sequences with intermittent observations using marked temporal point processes
A large fraction of data generated via human activities such as online purchases, health
records, spatial mobility, etc. can be represented as a sequence of events over a continuous …
records, spatial mobility, etc. can be represented as a sequence of events over a continuous …
Deep neyman-scott processes
A Neyman-Scott process is a special case of a Cox process. The latent and observable
stochastic processes are both Poisson processes. We consider a deep Neyman-Scott …
stochastic processes are both Poisson processes. We consider a deep Neyman-Scott …
Cyber risk modeling using a two-phase Hawkes process with external excitation
A Boumezoued, Y Cherkaoui, C Hillairet - arXiv preprint arXiv:2311.15701, 2023 - arxiv.org
With the growing digital transformation of the worldwide economy, cyber risk has become a
major issue. As 1% of the world's GDP (around $1,000 billion) is allegedly lost to cybercrime …
major issue. As 1% of the world's GDP (around $1,000 billion) is allegedly lost to cybercrime …
Hawkes processes modeling, inference, and control: An overview
R Lima - SIAM Review, 2023 - SIAM
Hawkes processes are a type of point process that models self-excitement among time
events. They have been used in a myriad of applications, ranging from finance and …
events. They have been used in a myriad of applications, ranging from finance and …
Multivariate Hawkes processes for incomplete biased data
Multivariate Hawkes processes have been widely used in many applications such as crime
detection and disaster rescue forecast to model events that exhibit self-exciting properties …
detection and disaster rescue forecast to model events that exhibit self-exciting properties …