Stabilizing generative adversarial networks: A survey M Wiatrak, SV Albrecht, A Nystrom arXiv preprint arXiv:1910.00927, 2019 | 115 | 2019 |
Simple hierarchical multi-task neural end-to-end entity linking for biomedical text M Wiatrak, J Iso-Sipila Proceedings of the 11th International Workshop on Health Text Mining and …, 2020 | 17 | 2020 |
Directed graph embeddings in pseudo-riemannian manifolds A Sim, ML Wiatrak, A Brayne, P Creed, S Paliwal International Conference on Machine Learning, 9681-9690, 2021 | 14 | 2021 |
On masked language models for contextual link prediction A Brayne, M Wiatrak, D Corneil Proceedings of Deep Learning Inside Out (DeeLIO 2022): The 3rd Workshop on …, 2022 | 5 | 2022 |
Proxy-based zero-shot entity linking by effective candidate retrieval M Wiatrak, E Arvaniti, A Brayne, J Vetterle, A Sim arXiv preprint arXiv:2301.13318, 2023 | 2 | 2023 |
Sequence-based modelling of bacterial genomes enables accurate antibiotic resistance prediction M Wiatrak, A Weimann, AM Dinan, M Brbić, RA Floto bioRxiv, 2024.01. 03.574022, 2024 | | 2024 |
Graph embedding systems and apparatus SIM Aaron, ML Wiatrak, ARG Brayne, P Creed, S Paliwal US Patent App. 18/365,325, 2023 | | 2023 |
Pseudo-Riemannian Embedding Models for Multi-Relational Graph Representations S Paliwal, A Brayne, B Fabian, M Wiatrak, A Sim arXiv preprint arXiv:2212.03720, 2022 | | 2022 |