Laurence Aitchison
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
22
Venues
4
Active years
2019–2025
Best venue rank
A*
Where they publish
Papers
22 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Residual Stream Analysis with Multi-Layer SAEs. | Tim Lawson, Lucy Farnik, Conor J. Houghton, Laurence Aitchison |
| 2025 | ICML | Position: Don't Use the CLT in LLM Evals With Fewer Than a Few Hundred Datapoints. | Sam Bowyer, Laurence Aitchison, Desi R. Ivanova |
| 2025 | ICML | Jacobian Sparse Autoencoders: Sparsify Computations, Not Just Activations. | Lucy Farnik, Tim Lawson, Conor J. Houghton, Laurence Aitchison |
| 2025 | ICML | Function-Space Learning Rates. | Edward Milsom, Ben Anson, Laurence Aitchison |
| 2025 | ICML | How to set AdamW's weight decay as you scale model and dataset size. | Xi Wang, Laurence Aitchison |
| 2024 | ICLR | Convolutional Deep Kernel Machines. | Edward Milsom, Ben Anson, Laurence Aitchison |
| 2024 | ICLR | Bayesian Low-rank Adaptation for Large Language Models. | Adam X. Yang, Maxime Robeyns, Xi Wang, Laurence Aitchison |
| 2024 | ICML | Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI. | Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, Jos Miguel Hernndez-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rgamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang |
| 2024 | UAI | Using Autodiff to Estimate Posterior Moments, Marginals and Samples. | Sam Bowyer, Thomas Heap, Laurence Aitchison |
| 2023 | ICLR | Semi-supervised learning with a principled likelihood from a generative model of data curation. | Stoil Ganev, Laurence Aitchison |
| 2023 | ICLR | Robustness to corruption in pre-trained Bayesian neural networks. | Xi Wang, Laurence Aitchison |
| 2023 | ICML | A theory of representation learning gives a deep generalisation of kernel methods. | Adam X. Yang, Maxime Robeyns, Edward Milsom, Ben Anson, Nandi Schoots, Laurence Aitchison |
| 2023 | UAI | Massively parallel reweighted wake-sleep. | Thomas Heap, Gavin Leech, Laurence Aitchison |
| 2023 | UAI | An improved variational approximate posterior for the deep Wishart process. | Sebastian W. Ober, Ben Anson, Edward Milsom, Laurence Aitchison |
| 2022 | ICLR | Bayesian Neural Network Priors Revisited. | Vincent Fortuin, Adri Garriga-Alonso, Sebastian W. Ober, Florian Wenzel, Gunnar Rtsch, Richard E. Turner, Mark van der Wilk, Laurence Aitchison |
| 2022 | UAI | Data augmentation in Bayesian neural networks and the cold posterior effect. | Seth Nabarro, Stoil Ganev, Adri Garriga-Alonso, Vincent Fortuin, Mark van der Wilk, Laurence Aitchison |
| 2021 | CoRL | Tactile Image-to-Image Disentanglement of Contact Geometry from Motion-Induced Shear. | Anupam K. Gupta, Laurence Aitchison, Nathan F. Lepora |
| 2021 | ICLR | A statistical theory of cold posteriors in deep neural networks. | Laurence Aitchison |
| 2021 | ICML | Deep Kernel Processes. | Laurence Aitchison, Adam X. Yang, Sebastian W. Ober |
| 2021 | ICML | Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes. | Sebastian W. Ober, Laurence Aitchison |
| 2020 | ICML | Why bigger is not always better: on finite and infinite neural networks. | Laurence Aitchison |
| 2019 | ICLR | Deep Convolutional Networks as shallow Gaussian Processes. | Adri Garriga-Alonso, Carl Edward Rasmussen, Laurence Aitchison |