| MM1: methods, analysis and insights from multimodal LLM pre-training B McKinzie, Z Gan, JP Fauconnier, S Dodge, B Zhang, P Dufter, D Shah, ... European Conference on Computer Vision, 304-323, 2024 | 180 | 2024 |
| Variational inference for Gaussian process modulated Poisson processes C Lloyd, T Gunter, M Osborne, S Roberts International Conference on Machine Learning, 1814-1822, 2015 | 144 | 2015 |
| Sampling for inference in probabilistic models with fast Bayesian quadrature T Gunter, MA Osborne, R Garnett, P Hennig, SJ Roberts Advances in neural information processing systems 27, 2014 | 124 | 2014 |
| Efficient Bayesian nonparametric modelling of structured point processes T Gunter, C Lloyd, MA Osborne, SJ Roberts arXiv preprint arXiv:1407.6949, 2014 | 42 | 2014 |
| Apple intelligence foundation language models T Gunter, Z Wang, C Wang, R Pang, A Narayanan, A Zhang, B Zhang, ... arXiv preprint arXiv:2407.21075, 2024 | 29 | 2024 |
| Blitzkriging: Kronecker-structured stochastic Gaussian processes T Nickson, T Gunter, C Lloyd, MA Osborne, S Roberts arXiv preprint arXiv:1510.07965, 2015 | 26 | 2015 |
| STAIR: learning sparse text and image representation in grounded tokens C Chen, B Zhang, L Cao, J Shen, T Gunter, AM Jose, A Toshev, J Shlens, ... arXiv preprint arXiv:2301.13081, 2023 | 20 | 2023 |
| Latent point process allocation C Lloyd, T Gunter, M Osborne, S Roberts, T Nickson Artificial Intelligence and Statistics, 389-397, 2016 | 20 | 2016 |
| Masked autoencoding does not help natural language supervision at scale F Weers, V Shankar, A Katharopoulos, Y Yang, T Gunter Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 13 | 2023 |
| Unknowable manipulators: Social network curator algorithms S Albanie, H Shakespeare, T Gunter arXiv preprint arXiv:1701.04895, 2017 | 13 | 2017 |
| Mobile V-MoEs: Scaling Down Vision Transformers via Sparse Mixture-of-Experts E Daxberger, F Weers, B Zhang, T Gunter, R Pang, M Eichner, ... arXiv preprint arXiv:2309.04354, 2023 | 7 | 2023 |
| On modelling uncertainty in neural language generation for policy optimisation in voice-triggered dialog assistants S Wang, T Gunter, D VanDyke 2nd Workshop on Conversational AI: Today’s Practice and Tomorrow’s Potential …, 2018 | 7 | 2018 |
| Large Language Model-guided Document Selection X Kong, T Gunter, R Pang arXiv preprint arXiv:2406.04638, 2024 | 2 | 2024 |
| Self supervision does not help natural language supervision at scale F Weers, V Shankar, A Katharopoulos, Y Yang, T Gunter arXiv preprint arXiv:2301.07836 10, 2023 | 1 | 2023 |
| Revisiting MoE and Dense Speed-Accuracy Comparisons for LLM Training X Du, T Gunter, X Kong, M Lee, Z Wang, A Zhang, N Du, R Pang arXiv preprint arXiv:2405.15052, 2024 | | 2024 |
| Structured Priors for Policy Optimisation S Wang, B Byrne, T Gunter | | 2017 |
| Towards efficient Bayesian inference: Cox processes and probabilistic integration T Gunter University of Oxford, 2017 | | 2017 |
