3 papers
cs.LG2025
Stick-Breaking Embedded Topic Model with Continuous Optimal Transport for Online Analysis of Document Streams
Federica Granese, Serena Villata, Charles Bouveyron
Online topic models are unsupervised algorithms to identify latent topics in data streams that continuously evolve over time. Although these methods naturally align with real-world…
cs.LG2025
Merging Embedded Topics with Optimal Transport for Online Topic Modeling on Data Streams
Federica Granese, Benjamin Navet, Serena Villata +1
Topic modeling is a key component in unsupervised learning, employed to identify topics within a corpus of textual data. The rapid growth of social media generates an ever-growing…
stat.ME2024
The Deep Latent Position Block Model For The Block Clustering And Latent Representation Of Networks
Rémi Boutin, Pierre Latouche, Charles Bouveyron
The increased quantity of data has led to a soaring use of networks to model relationships between different objects, represented as nodes. Since the number of nodes can be particu…