| Neural embeddings of graphs in hyperbolic space BP Chamberlain, J Clough, MP Deisenroth arXiv preprint arXiv:1705.10359, 2017 | 104 | 2017 |
| 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 Knowledge …, 2017 | 52 | 2017 |
| 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 | 37 | 2018 |
| SIGN: Scalable Inception Graph Neural Networks F Frasca, E Rossi, D Eynard, B Chamberlain, M Bronstein, F Monti arXiv e-prints, arXiv: 2004.11198, 2020 | 19* | 2020 |
| Scalable hyperbolic recommender systems BP Chamberlain, SR Hardwick, DR Wardrope, F Dzogang, F Daolio, ... arXiv preprint arXiv:1902.08648, 2019 | 16 | 2019 |
| 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 in …, 2017 | 16* | 2017 |
| 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 | 15 | 2020 |
| 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 | 14 | 2018 |
| Generalising random forest parameter optimisation to include stability and cost CHB Liu, BP Chamberlain, DA Little, Â Cardoso Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017 | 11 | 2017 |
| Learning Embeddings for Product Size Recommendations K Dogani, M Tomassetti, S De Cnudde, S Vargas, B Chamberlain eCOM@SIGIR, 2019 | 5 | 2019 |
| Fashion Outfit Generation for E-commerce EM Bettaney, SR Hardwick, O Zisimopoulos, BP Chamberlain Joint European Conference on Machine Learning and Knowledge Discovery in …, 2019 | 4 | 2019 |
| A recurrent neural network survival model: Predicting web user return time GL Grob, Â Cardoso, CHB Liu, DA Little, BP Chamberlain Joint European Conference on Machine Learning and Knowledge Discovery in …, 2018 | 4 | 2018 |
| Designing experiments to measure incrementality on facebook CH Liu, EM Bettaney, BP Chamberlain arXiv preprint arXiv:1806.02588, 2018 | 3 | 2018 |
| Online Controlled Experiments for Personalised e-Commerce Strategies: Design, Challenges, and Pitfalls CH Liu, BP Chamberlain arXiv preprint arXiv:1803.06258, 2018 | 3 | 2018 |
| On overlapping community-based networks: generation, detection, and their applications CHB Liu, MP Deisenroth, BP Chamberlain Master’s thesis, Imperial College London, London, United Kingdom, 2016 | 3 | 2016 |
| 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 | 1 | 2020 |
| What is the value of experimentation & measurement? CH Liu, BP Chamberlain IEEE International Conference on Data Mining (ICDM) 2019, 2019 | 1 | 2019 |
| Speeding up bigclam implementation on snap CH Liu, BP Chamberlain arXiv preprint arXiv:1712.01209, 2017 | 1 | 2017 |
| What is the Value of Experimentation and Measurement? Quantifying the Value and Risk of Reducing Uncertainty to Make Better Decisions CHB Liu, BP Chamberlain, EJ McCoy Data Science and Engineering 5, 152-167, 2020 | | 2020 |
| Practical challenges of learning and representation for large graphs BP Chamberlain University of London, 2018 | | 2018 |
Marc DeisenrothUniversity College LondonVerified email at ucl.ac.uk
