activity
20152026
most citedA Tutorial on Hawkes Processes for Events in Social Media

61 citations · 140 across the 36 of their papers we have counts for

collaborators
Showing cs.LGShow all

5 papers · 1 filter

cs.LG2024

What Drives Online Popularity: Author, Content or Sharers? Estimating Spread Dynamics with Bayesian Mixture Hawkes

Pio Calderon, Marian-Andrei Rizoiu

The spread of content on social media is shaped by intertwining factors on three levels: the source, the content itself, and the pathways of content spread. At the lowest level, th…

cs.LG2019

Quantile Propagation for Wasserstein-Approximate Gaussian Processes

Rui Zhang, Christian J. Walder, Edwin V. Bonilla +2

Approximate inference techniques are the cornerstone of probabilistic methods based on Gaussian process priors. Despite this, most work approximately optimizes standard divergence…

cs.LG2019

Motorway Traffic Flow Prediction using Advanced Deep Learning

Adriana-Simona Mihaita, Haowen Li, Zongyang He +1

Congestion prediction represents a major priority for traffic management centres around the world to ensure timely incident response handling. The increasing amounts of generated t…

cs.LG201922 cited

Arterial incident duration prediction using a bi-level framework of extreme gradient-tree boosting

Adriana-Simona Mihaita, Zheyuan Liu, Chen Cai +1

Predicting traffic incident duration is a major challenge for many traffic centres around the world. Most research studies focus on predicting the incident duration on motorways ra…

cs.LG2019

Variational Inference for Sparse Gaussian Process Modulated Hawkes Process

Rui Zhang, Christian Walder, Marian-Andrei Rizoiu

The Hawkes process (HP) has been widely applied to modeling self-exciting events including neuron spikes, earthquakes and tweets. To avoid designing parametric triggering kernel an…