Agrin Hilmkil
Agrin Hilmkil
Microsoft Research
Bestätigte E-Mail-Adresse bei - Startseite
Zitiert von
Zitiert von
Understanding causality with large language models: Feasibility and opportunities
C Zhang, S Bauer, P Bennett, J Gao, W Gong, A Hilmkil, J Jennings, C Ma, ...
arXiv preprint arXiv:2304.05524, 2023
Scaling federated learning for fine-tuning of large language models
A Hilmkil, S Callh, M Barbieri, LR Sütfeld, EL Zec, O Mogren
International Conference on Applications of Natural Language to Information …, 2021
Towards machine learning on data from professional cyclists
A Hilmkil, O Ivarsson, M Johansson, D Kuylenstierna, T van Erp
arXiv preprint arXiv:1808.00198, 2018
SHIBR—The Swedish historical birth records: A semi-annotated dataset
A Cheddad, H Kusetogullari, A Hilmkil, L Sundin, A Yavariabdi, ...
Neural Computing and Applications 33, 15863-15875, 2021
Causal reasoning in the presence of latent confounders via neural admg learning
M Ashman, C Ma, A Hilmkil, J Jennings, C Zhang
arXiv preprint arXiv:2303.12703, 2023
A causal AI suite for decision-making
E Kiciman, EW Dillon, D Edge, A Foster, A Hilmkil, J Jennings, C Ma, ...
NeurIPS 2022 Workshop on Causality for Real-world Impact, 2022
Perceiving music quality with gans
A Hilmkil, C Thomé, A Arpteg
arXiv preprint arXiv:2006.06287, 2020
The Essential Role of Causality in Foundation World Models for Embodied AI
T Gupta, W Gong, C Ma, N Pawlowski, A Hilmkil, M Scetbon, A Famoti, ...
arXiv preprint arXiv:2402.06665, 2024
Learned Causal Method Prediction
S Gupta, C Zhang, A Hilmkil
arXiv preprint arXiv:2311.03989, 2023
FiP: a Fixed-Point Approach for Causal Generative Modeling
M Scetbon, J Jennings, A Hilmkil, C Zhang, C Ma
arXiv preprint arXiv:2404.06969, 2024
Modelling causation in machine learning
G Wenbo, C Zhang, N Pawlowski, J Jennings, K Fassio, M Defante, ...
US Patent App. 17/936,347, 2024
Modelling causation in machine learning
C Ma, C Zhang, M Ashman, M Defante, K Fassio, J Jennings, A Hilmkil
US Patent App. 17/936,338, 2024
Towards Machine Learning on Data from Professional Cyclists
O Ivarsson, A Hilmkil, M Johansson
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