Benjamin Paul Chamberlain | DeepAI

AI Chat

Featured Co-authors

Pietro Liò
159 publications
Marc Peter Deisenroth
60 publications
Michael M. Bronstein
60 publications
Nikolaos Aletras
52 publications
Xiaowen Dong
43 publications
Michael Bronstein
38 publications
Cristian Bodnar
14 publications
Fabrizio Frasca
12 publications
Nils Hammerla
11 publications
Emanuele Rossi
11 publications
C. H. Bryan Liu
10 publications

∙ 09/30/2022

Graph Neural Networks for Link Prediction with Subgraph Sketching

Many Graph Neural Networks (GNNs) perform poorly compared to simple heur...

56 Benjamin Paul Chamberlain, et al. ∙

∙ 02/09/2022

Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs

Cellular sheaves equip graphs with "geometrical" structure by assigning ...

120 Cristian Bodnar, et al. ∙

∙ 11/29/2021

Understanding over-squashing and bottlenecks on graphs via curvature

Most graph neural networks (GNNs) use the message passing paradigm, in w...

1 Jake Topping, et al. ∙

∙ 11/23/2021

On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features

While Graph Neural Networks (GNNs) have recently become the de facto sta...

17 Emanuele Rossi, et al. ∙

∙ 10/18/2021

Beltrami Flow and Neural Diffusion on Graphs

We propose a novel class of graph neural networks based on the discretis...

74 Benjamin Paul Chamberlain, et al. ∙

∙ 06/21/2021

GRAND: Graph Neural Diffusion

We present Graph Neural Diffusion (GRAND) that approaches deep learning ...

129 Benjamin Paul Chamberlain, et al. ∙

∙ 09/08/2019

What is the value of experimentation measurement?

Experimentation and Measurement (E M) capabilities allow organizations...

0 C. H. Bryan Liu, et al. ∙

∙ 02/22/2019

Scalable Hyperbolic Recommender Systems

We present a large scale hyperbolic recommender system. We discuss why h...

0 Benjamin Paul Chamberlain, et al. ∙

∙ 07/11/2018

A Recurrent Neural Network Survival Model: Predicting Web User Return Time

The size of a website's active user base directly affects its value. Thu...

0 Georg L. Grob, et al. ∙

∙ 06/07/2018

Designing Experiments to Measure Incrementality on Facebook

The importance of Facebook advertising has risen dramatically in recent ...

0 C. H. Bryan Liu, et al. ∙

∙ 04/11/2018

Predicting Twitter User Socioeconomic Attributes with Network and Language Information

Inferring socioeconomic attributes of social media users such as occupat...

0 Nikolaos Aletras, et al. ∙

∙ 03/16/2018

Online Controlled Experiments for Personalised e-Commerce Strategies: Design, Challenges, and Pitfalls

Online controlled experiments are the primary tool for measuring the cau...

0 C. H. Bryan Liu, et al. ∙

∙ 12/04/2017

Speeding Up BigClam Implementation on SNAP

We perform a detailed analysis of the C++ implementation of the Cluster ...

0 C. H. Bryan Liu, et al. ∙

∙ 06/29/2017

Generalising Random Forest Parameter Optimisation to Include Stability and Cost

Random forests are among the most popular classification and regression ...

0 C. H. Bryan Liu, et al. ∙

∙ 05/29/2017

Neural Embeddings of Graphs in Hyperbolic Space

Neural embeddings have been used with great success in Natural Language ...

0 Benjamin Paul Chamberlain, et al. ∙

∙ 03/07/2017

Customer Lifetime Value Prediction Using Embeddings

We describe the Customer LifeTime Value (CLTV) prediction system deploye...

0 Benjamin Paul Chamberlain, et al. ∙

∙ 01/18/2016

Probabilistic Inference of Twitter Users' Age based on What They Follow

Twitter provides an open and rich source of data for studying human beha...

0 Benjamin Paul Chamberlain, et al. ∙

∙ 01/15/2016

Real-Time Community Detection in Large Social Networks on a Laptop

For a broad range of research, governmental and commercial applications ...

0 Benjamin Paul Chamberlain, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world