Benjamin Paul Chamberlain
Benjamin Paul Chamberlain
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Temporal graph networks for deep learning on dynamic graphs
E Rossi, B Chamberlain, F Frasca, D Eynard, F Monti, M Bronstein
arXiv preprint arXiv:2006.10637, 2020
Neural embeddings of graphs in hyperbolic space
BP Chamberlain, J Clough, MP Deisenroth
arXiv preprint arXiv:1705.10359, 2017
Sign: Scalable inception graph neural networks
E Rossi, F Frasca, B Chamberlain, D Eynard, M Bronstein, F Monti
arXiv preprint arXiv:2004.11198 7, 15, 2020
Customer lifetime value prediction using embeddings
BP Chamberlain, A Cardoso, CHB Liu, R Pagliari, MP Deisenroth
Proceedings of the 23rd ACM SIGKDD international conference on knowledgeá…, 2017
Sign: Scalable inception graph neural networks
F Frasca, E Rossi, D Eynard, B Chamberlain, M Bronstein, F Monti
arXiv preprint arXiv:2004.11198, 2020
Predicting twitter user socioeconomic attributes with network and language information
N Aletras, BP Chamberlain
Proceedings of the 29th on Hypertext and Social Media, 20-24, 2018
GRAND: Graph Neural Diffusion
BP Chamberlain, J Rowbottom, M Gorinova, S Webb, E Rossi, ...
The 38th International Conference on Machine Learning (ICML 2021), 2021
Scalable hyperbolic recommender systems
BP Chamberlain, SR Hardwick, DR Wardrope, F Dzogang, F Daolio, ...
arXiv preprint arXiv:1902.08648, 2019
Understanding over-squashing and bottlenecks on graphs via curvature
J Topping, F Di Giovanni, BP Chamberlain, X Dong, MM Bronstein
The Tenth International Conference on Learning Representations (ICLR 2022), 2021
Generalising random forest parameter optimisation to include stability and cost
CH Liu, BP Chamberlain, DA Little, ┬ Cardoso
Joint European Conference on Machine Learning and Knowledge Discovery iná…, 2017
Real-time community detection in full social networks on a laptop
BP Chamberlain, J Levy-Kramer, C Humby, MP Deisenroth
PloS one 13 (1), e0188702, 2018
Probabilistic inference of twitter users’ age based on what they follow
BP Chamberlain, C Humby, MP Deisenroth
Joint European Conference on Machine Learning and Knowledge Discovery iná…, 2017
Fashion Outfit Generation for E-commerce
EM Bettaney, SR Hardwick, O Zisimopoulos, BP Chamberlain
Joint European Conference on Machine Learning and Knowledge Discovery iná…, 2019
Learning Embeddings for Product Size Recommendations
K Dogani, M Tomassetti, S De Cnudde, S Vargas, B Chamberlain
eCOM@SIGIR, 2019
A recurrent neural network survival model: Predicting web user return time
GL Grob, ┬ Cardoso, CH Liu, DA Little, BP Chamberlain
Joint European Conference on Machine Learning and Knowledge Discovery iná…, 2018
Beltrami Flow and Neural Diffusion on Graphs
BP Chamberlain, J Rowbottom, D Eynard, F Di Giovanni, X Dong, ...
35th Conference on Neural Information Processing Systems (NeurIPS 2021), 2021
RecSys 2021 Challenge Workshop: Fairness-aware engagement prediction at scale on Twitter’s Home Timeline
VW Anelli, S Kalloori, B Ferwerda, L Belli, A Tejani, F Portman, ...
Fifteenth ACM Conference on Recommender Systems, 819-824, 2021
Tuning Word2vec for Large Scale Recommendation Systems
BP Chamberlain, E Rossi, D Shiebler, S Sedhain, MM Bronstein
In Fourteenth ACM Conference on Recommender Systems (pp. 732-737), 2020
On the unreasonable effectiveness of feature propagation in learning on graphs with missing node features
E Rossi, H Kenlay, MI Gorinova, BP Chamberlain, X Dong, M Bronstein
arXiv preprint arXiv:2111.12128, 2021
The 2021 RecSys Challenge Dataset: Fairness is not optional
L Belli, A Tejani*, F Portman*, A Lung-Yut-Fong*, B Chamberlain, Y Xie, ...
RecSysChallenge'21: Proceedings of the Recommender Systems Challenge 2021, 1-6, 2021
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