| Tucker: Tensor factorization for knowledge graph completion I Balažević, C Allen, TM Hospedales EMNLP, 2019 | 973 | 2019 |
| Multi-scale attributed node embedding B Rozemberczki, C Allen, R Sarkar Journal of Complex Networks 9 (2), cnab014, 2021 | 820 | 2021 |
| Multi-relational poincaré graph embeddings I Balazevic, C Allen, T Hospedales Advances in Neural Information Processing Systems 32, 2019 | 372 | 2019 |
| Hypernetwork knowledge graph embeddings I Balažević, C Allen, TM Hospedales Artificial Neural Networks and Machine Learning–ICANN 2019: Workshop and …, 2019 | 247 | 2019 |
| Analogies Explained: Towards Understanding Word Embeddings C Allen, T Hospedales International Conference on Machine Learning 97, 223-231, 2019 | 174 | 2019 |
| Biomimetic synthesis of lantibiotics S Burrage, T Raynham, G Williams, JW Essex, C Allen, M Cardno, V Swali, ... Chemistry–A European Journal 6 (8), 1455-1466, 2000 | 109 | 2000 |
| Benchmark and best practices for biomedical knowledge graph embeddings D Chang, I Balažević, C Allen, D Chawla, C Brandt, RA Taylor Proceedings of the conference. Association for Computational Linguistics …, 2020 | 50 | 2020 |
| Interpreting knowledge graph relation representation from word embeddings C Allen, I Balažević, T Hospedales arXiv preprint arXiv:1909.11611, 2019 | 34* | 2019 |
| What the Vec? Towards Probabilistically Grounded Embeddings C Allen, I Balažević, T Hospedales arXiv preprint arXiv:1805.12164, 2019 | 33 | 2019 |
| Adapters for enhanced modeling of multilingual knowledge and text Y Hou, W Jiao, M Liu, C Allen, Z Tu, M Sachan arXiv preprint arXiv:2210.13617, 2022 | 7 | 2022 |
| A Probabilistic Model for Discriminative and Neuro-Symbolic Semi-Supervised Learning C Allen, I Balažević, T Hospedales arXiv preprint arXiv:2006.05896, 2020 | 6 | 2020 |
| Variational classification: A probabilistic generalization of the softmax classifier SZ Dhuliawala, M Sachan, C Allen Transactions on Machine Learning Research, 2024 | 5* | 2024 |
| Learning to drop out: An adversarial approach to training sequence vaes D Miladinovic, K Shridhar, K Jain, M Paulus, JM Buhmann, C Allen Advances in Neural Information Processing Systems 35, 9645-9659, 2022 | 2 | 2022 |
| A Probabilistic Model to explain Self-Supervised Representation Learning A Bizeul, B Schölkopf, C Allen arXiv preprint arXiv:2402.01399, 2024 | | 2024 |
| Method and apparatus for semi-supervised learning I Balazevic, C Allen, T Hospedales US Patent App. 17/436,927, 2023 | | 2023 |
| Towards a theoretical understanding of word and relation representation C Allen arXiv preprint arXiv:2202.00486, 2022 | | 2022 |
| Learning the Prediction Distribution for Semi-Supervised Learning with Normalising Flows I Balažević, C Allen, T Hospedales arXiv preprint arXiv:2007.02745, 2020 | | 2020 |
| SimVAE: Narrowing the gap between Discriminative & Generative Representation Learning A Bizeul, C Allen NeurIPS 2023 Workshop on Mathematics of Modern Machine Learning, 0 | | |
Timothy M. HospedalesProfessor, University of Edinburgh; Samsung AI ResearchVerified email at ed.ac.uk
