Pascal Notin
Pascal Notin
Department of Computer Science, University of Oxford
Verified email at - Homepage
Cited by
Cited by
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
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
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
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
Learning from prepandemic data to forecast viral escape
NN Thadani, S Gurev, P Notin, N Youssef, NJ Rollins, D Ritter, C Sander, ...
Nature 622 (7984), 818-825, 2023
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
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
ProteinGym: Large-scale Benchmarks for Protein Fitness Prediction and Design
P Notin, A Kollasch, D Ritter, L Van Niekerk, S Paul, H Spinner, N Rollins, ...
Advances in Neural Information Processing Systems 36, 2024
TranceptEVE: Combining Family-specific and Family-agnostic Models of Protein Sequences for Improved Fitness Prediction
PM Notin, L Van Niekerk, AW Kollasch, D Ritter, Y Gal, D Marks
NeurIPS, LMRL workshop, 2022
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
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 36, 2024
Machine learning for functional protein design
P Notin, N Rollins, Y Gal, C Sander, D Marks
Nature Biotechnology 42 (2), 216-228, 2024
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
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
Improving compute efficacy frontiers with SliceOut
P Notin, AN Gomez, J Yoo, Y Gal
arXiv preprint arXiv:2007.10909, 2020
Sampling protein language models for functional protein design
JT Darmawan, Y Gal, P Notin
NeurIPS 2023 Generative AI and Biology (GenBio) Workshop, 2023
Protein design for evaluating vaccines against future viral variation
N Youssef, S Gurev, F Ghantous, K Brock, J Jaimes, NN Thadani, ...
bioRxiv, 2023.10. 08.561389, 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, 2023
DyNeMoC: A semi-supervised architecture for classifying time series brain data
AMS Khan, C Gohil, P Notin, J van Amersfoort, M Woolrich, Y Gal
ICLR 2023 Workshop on Time Series Representation Learning for Health, 2023
Deep generative models for biology: represent, predict, design
P Notin
University of Oxford, 2023
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