| Disease variant prediction with deep generative models of evolutionary data J Frazer*, P Notin*, M Dias*, A Gomez, JK Min, K Brock, Y Gal, DS Marks Nature 599 (7883), 91-95, 2021 | 464 | 2021 |
| Tranception: Protein Fitness Prediction with Autoregressive Transformers and Inference-time Retrieval P Notin, M Dias, J Frazer, JM Hurtado, AN Gomez, D Marks, Y Gal International Conference on Machine Learning (ICML), 16990-17017, 2022 | 146 | 2022 |
| RITA: a Study on Scaling Up Generative Protein Sequence Models D Hesslow, N Zanichelli, P Notin, I Poli, D Marks ICML, Workshop on Computational Biology (WCB), 2022 | 58* | 2022 |
| Improving black-box optimization in VAE latent space using decoder uncertainty P Notin, JM Hernández-Lobato, Y Gal Advances in Neural Information Processing Systems (NeurIPS) 34, 802-814, 2021 | 51 | 2021 |
| Learning from prepandemic data to forecast viral escape NN Thadani*, S Gurev*, P Notin*, N Youssef, NJ Rollins, D Ritter, ... Nature 622 (7984), 818-825, 2023 | 49* | 2023 |
| ProteinGym: Large-scale Benchmarks for Protein Fitness Prediction and Design P Notin*, A Kollasch*, D Ritter*, L Van Niekerk*, S Paul, H Spinner, ... Advances in Neural Information Processing Systems 36, 2024 | 45* | 2024 |
| TranceptEVE: Combining Family-specific and Family-agnostic Models of Protein Sequences for Improved Fitness Prediction P Notin, L Van Niekerk, AW Kollasch, D Ritter, Y Gal, D Marks NeurIPS, LMRL workshop, 2022 | 18 | 2022 |
| Mixtures of large-scale dynamic functional brain network modes C Gohil, E Roberts, R Timms, A Skates, C Higgins, A Quinn, U Pervaiz, ... NeuroImage, 2022 | 16 | 2022 |
| GeneDisco: A Benchmark for Experimental Design in Drug Discovery A Mehrjou, A Soleymani, A Jesson, P Notin, Y Gal, S Bauer, P Schwab International Conference on Learning Representations (ICLR), 2021 | 16 | 2021 |
| Machine learning for functional protein design P Notin*, N Rollins*, Y Gal, C Sander, D Marks Nature Biotechnology 42 (2), 216-228, 2024 | 15 | 2024 |
| ProteinNPT: improving protein property prediction and design with non-parametric transformers P Notin*, R Weitzman*, D Marks, Y Gal Advances in Neural Information Processing Systems (NeurIPS) 36, 33529-33563, 2023 | 9 | 2023 |
| DiscoBAX Discovery of optimal intervention sets in genomic experiment design C Lyle*, A Mehrjou*, P Notin*, A Jesson, S Bauer, Y Gal, P Schwab International Conference on Machine Learning, 23170-23189, 2023 | 5 | 2023 |
| Principled uncertainty estimation for high dimensional data P Notin, JM Hernández-Lobato, Y Gal ICML, Workshop on Uncertainty and Robustness in Deep Learning (UDL), 2020 | 5 | 2020 |
| The CausalBench challenge: A machine learning contest for gene network inference from single-cell perturbation data M Chevalley, J Sackett-Sanders, Y Roohani, P Notin, A Bakulin, ... arXiv preprint arXiv:2308.15395, 2023 | 3 | 2023 |
| Improving compute efficacy frontiers with SliceOut P Notin, AN Gomez, J Yoo, Y Gal arXiv preprint arXiv:2007.10909, 2020 | 3* | 2020 |
| Deep generative models predict SARS-CoV-2 spike infectivity and foreshadow neutralizing antibody escape N Youssef, F Ghantous, S Gurev, K Brock, JA Jaimes, A Dauphin, ... bioRxiv, 2023 | 2* | 2023 |
| Sampling protein language models for functional protein design JT Darmawan, Y Gal, P Notin NeurIPS 2023 Generative AI and Biology (GenBio) Workshop, 2023 | 2 | 2023 |
| Combining Structure and Sequence for Superior Fitness Prediction S Paul, A Kollasch, P Notin, D Marks NeurIPS 2023 Generative AI and Biology (GenBio) Workshop, 0 | 2 | |
| Deep generative models for biology: represent, predict, design P Notin University of Oxford, 2023 | | 2023 |
| Augmenting Evolutionary Models with Structure-based Retrieval Y Huang, Z Zhang, J Tang, DS Marks, P Notin ICML'24 Workshop ML for Life and Material Science: From Theory to Industry …, 0 | | |
Yarin GalAssociate Professor, University of OxfordVerified email at cs.ox.ac.uk
