Patrick Rubin‐Delanchy

1. A statistical interpretation of spectral embedding: the generalised random dot product graph
   2017/09/16 by Patrick Rubin‐Delanchy, Joshua Cape, Rubin-Delanchy, Patrick +5 · 12 citations
   Computer Science · Physics and Astronomy · #62E20 #62H12 #62H30 #Advanced Graph Neural Networks #Complex Network Analysis Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Opinion Dynamics and Social Influence
2. The multilayer random dot product graph
   2020/07/20 by A. Jones, Jones, Andrew, Patrick Rubin‐Delanchy +1 · 8 citations
   Computer Science · Mathematics · Physics and Astronomy · #Advanced Graph Neural Networks #Complex Network Analysis Techniques #FOS: Computer and information sciences #Graph theory and applications #Machine Learning (cs.LG) #Machine Learning (stat.ML)
3. Spectral embedding of weighted graphs
   2019/10/12 by Ian Gallagher, Gallagher, Ian, Andrew Jones +7 · 2 citations
   Physics and Astronomy · #Complex Network Analysis Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
4. Intensity Profile Projection: A Framework for Continuous-Time Representation Learning for Dynamic Networks
   2023/06/09 by Alexander Modell, Ian Gallagher, Modell, Alexander +7 · 2 citations
   Computer Science · Neuroscience · #Bayesian Modeling and Causal Inference #Functional Brain Connectivity Studies
5. Hierarchical clustering with dot products recovers hidden tree structure
   2023/05/24 by Annie Gray, Alexander Modell, Gray, Annie +5 · 1 citation
   Computer Science · #Advanced Clustering Algorithms Research #Data Management and Algorithms #Bayesian Methods and Mixture Models
6. A Simple and Powerful Framework for Stable Dynamic Network Embedding
   2023/11/14 by Edward Davis, Davis, Ed, Ian Gallagher +5 · 1 citation
   Physics and Astronomy · #62G99 (Secondary) #62H15 (Primary) 62H30 #62M10 #Complex Network Analysis Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Opinion Dynamics and Social Influence #Social and Information Networks (cs.SI)