| With or without you: predictive coding and Bayesian inference in the brain L Aitchison, M Lengyel Current opinion in neurobiology 46, 219-227, 2017 | 339 | 2017 |
| Deep convolutional networks as shallow Gaussian processes A Garriga-Alonso, CE Rasmussen, L Aitchison International Conference on Learning Representations 3, 2018 | 318 | 2018 |
| Understanding the effectiveness of government interventions against the resurgence of COVID-19 in Europe M Sharma, S Mindermann, C Rogers-Smith, G Leech, B Snodin, J Ahuja, ... Nature communications 12 (1), 5820, 2021 | 252 | 2021 |
| Doubly Bayesian analysis of confidence in perceptual decision-making L Aitchison, D Bang, B Bahrami, PE Latham PLoS computational biology 11 (10), e1004519, 2015 | 170 | 2015 |
| Bayesian neural network priors revisited V Fortuin, A Garriga-Alonso, SW Ober, F Wenzel, G Rätsch, RE Turner, ... arXiv preprint arXiv:2102.06571, 2021 | 169 | 2021 |
| Cortical-like dynamics in recurrent circuits optimized for sampling-based probabilistic inference R Echeveste, L Aitchison, G Hennequin, M Lengyel Nature neuroscience 23 (9), 1138-1149, 2020 | 142 | 2020 |
| Confidence matching in group decision-making D Bang, L Aitchison, R Moran, S Herce Castanon, B Rafiee, A Mahmoodi, ... Nature Human Behaviour 1 (6), 0117, 2017 | 132 | 2017 |
| Mask wearing in community settings reduces SARS-CoV-2 transmission G Leech, C Rogers-Smith, JT Monrad, JB Sandbrink, B Snodin, R Zinkov, ... Proceedings of the National Academy of Sciences 119 (23), e2119266119, 2022 | 116* | 2022 |
| Synaptic plasticity as Bayesian inference L Aitchison, J Jegminat, JA Menendez, JP Pfister, A Pouget, PE Latham Nature Neuroscience, 1-7, 2021 | 115* | 2021 |
| Zipf’s law arises naturally when there are underlying, unobserved variables L Aitchison, N Corradi, PE Latham PLoS computational biology 12 (12), e1005110, 2016 | 114* | 2016 |
| The Hamiltonian brain: Efficient probabilistic inference with excitatory-inhibitory neural circuit dynamics L Aitchison, M Lengyel PLoS computational biology 12 (12), e1005186, 2016 | 90 | 2016 |
| Fast sampling-based inference in balanced neuronal networks G Hennequin, L Aitchison, M Lengyel Advances in neural information processing systems 27, 2014 | 75 | 2014 |
| A statistical theory of cold posteriors in deep neural networks L Aitchison arXiv preprint arXiv:2008.05912, 2020 | 71 | 2020 |
| Active dendritic integration as a mechanism for robust and precise grid cell firing C Schmidt-Hieber, G Toleikyte, L Aitchison, A Roth, BA Clark, T Branco, ... Nature neuroscience 20 (8), 1114-1121, 2017 | 71 | 2017 |
| Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes SW Ober, L Aitchison International Conference on Machine Learning, 8248-8259, 2021 | 62 | 2021 |
| Why bigger is not always better: on finite and infinite neural networks L Aitchison International Conference on Machine Learning, 156-164, 2020 | 61 | 2020 |
| Deep kernel processes L Aitchison, A Yang, SW Ober International Conference on Machine Learning, 130-140, 2021 | 50 | 2021 |
| Position paper: Bayesian deep learning in the age of large-scale ai T Papamarkou, M Skoularidou, K Palla, L Aitchison, J Arbel, D Dunson, ... arXiv e-prints, arXiv: 2402.00809, 2024 | 40* | 2024 |
| Bayesian low-rank adaptation for large language models AX Yang, M Robeyns, X Wang, L Aitchison arXiv preprint arXiv:2308.13111, 2023 | 40 | 2023 |
| InfoNCE is variational inference in a recognition parameterised model L Aitchison, S Ganev arXiv preprint arXiv:2107.02495, 2021 | 37* | 2021 |
