Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ...
arXiv preprint arXiv:2403.05530, 2024
993 2024 Representation learning via invariant causal mechanisms J Mitrovic, B McWilliams, J Walker, L Buesing, C Blundell
arXiv preprint arXiv:2010.07922, 2020
278 2020 Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging S Azizi, L Culp, J Freyberg, B Mustafa, S Baur, S Kornblith, T Chen, ...
Nature Biomedical Engineering 7 (6), 756-779, 2023
162 2023 Causal reasoning from meta-reinforcement learning I Dasgupta, J Wang, S Chiappa, J Mitrovic, P Ortega, D Raposo, ...
arXiv preprint arXiv:1901.08162, 2019
134 2019 Pushing the limits of self-supervised resnets: Can we outperform supervised learning without labels on imagenet? N Tomasev, I Bica, B McWilliams, L Buesing, R Pascanu, C Blundell, ...
arXiv preprint arXiv:2201.05119, 2022
100 2022 Causal inference via kernel deviance measures J Mitrovic, D Sejdinovic, YW Teh
Advances in neural information processing systems 31, 2018
69 2018 Coberl: Contrastive bert for reinforcement learning A Banino, AP Badia, J Walker, T Scholtes, J Mitrovic, C Blundell
arXiv preprint arXiv:2107.05431, 2021
45 2021 DR-ABC: Approximate Bayesian computation with kernel-based distribution regression J Mitrovic, D Sejdinovic, YW Teh
International Conference on Machine Learning, 1482-1491, 2016
39 2016 Causally correct partial models for reinforcement learning DJ Rezende, I Danihelka, G Papamakarios, NR Ke, R Jiang, T Weber, ...
arXiv preprint arXiv:2002.02836, 2020
37 2020 Neural algorithmic reasoning with causal regularisation B Bevilacqua, K Nikiforou, B Ibarz, I Bica, M Paganini, C Blundell, ...
International Conference on Machine Learning, 2272-2288, 2023
27 2023 Encoders and ensembles for task-free continual learning M Shanahan, C Kaplanis, J Mitrović
arXiv preprint arXiv:2105.13327, 2021
24 2021 Hierarchical adversarially learned inference MI Belghazi, S Rajeswar, O Mastropietro, N Rostamzadeh, J Mitrovic, ...
arXiv preprint arXiv:1802.01071, 2018
24 2018 Less can be more in contrastive learning J Mitrovic, B McWilliams, M Rey
PMLR, 2020
23 2020 Amortized learning of neural causal representations NR Ke, J Wang, J Mitrovic, M Szummer, DJ Rezende
arXiv preprint arXiv:2008.09301, 2020
20 2020 Improving fine-grained understanding in image-text pre-training I Bica, A Ilić, M Bauer, G Erdogan, M Bošnjak, C Kaplanis, AA Gritsenko, ...
arXiv preprint arXiv:2401.09865, 2024
13 2024 Semppl: Predicting pseudo-labels for better contrastive representations M Bošnjak, PH Richemond, N Tomasev, F Strub, JC Walker, F Hill, ...
arXiv preprint arXiv:2301.05158, 2023
10 2023 Synth S Sharifzadeh, C Kaplanis, S Pathak, D Kumaran, A Ilic, J Mitrovic, ...
arXiv preprint arXiv:2403.07750, 2024
8 2024 Continually learning representations at scale A Galashov, J Mitrovic, D Tirumala, YW Teh, T Nguyen, A Chaudhry, ...
Conference on Lifelong Learning Agents, 534-547, 2023
6 2023 Deep Kernel Machines via the Kernel Reparametrization Trick J Mitrovic, D Sejdinovic, YW Teh
2 2017 Meta-reinforcement learning of causal strategies I Dasgupta, Z Kurth-Nelson, S Chiappa, J Mitrovic, P Ortega, E Hughes, ...
The Meta-Learning Workshop at the Neural Information Processing Systems …, 2019
1 2019 
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindZweryfikowany adres z stats.ox.ac.uk