| 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 | 48 | 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 | 40 | 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 | 20 | 2018 |
| 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 | 13 | 2023 |
| 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 | 12 | 2021 |
| The essential role of causality in foundation world models for embodied ai T Gupta, W Gong, C Ma, N Pawlowski, A Hilmkil, M Scetbon, M Rigter, ... arXiv preprint arXiv:2402.06665, 2024 | 10 | 2024 |
| 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 | 10 | 2022 |
| Towards causal foundation model: on duality between causal inference and attention J Zhang, J Jennings, A Hilmkil, N Pawlowski, C Zhang, C Ma arXiv preprint arXiv:2310.00809, 2023 | 9 | 2023 |
| Learned Causal Method Prediction S Gupta, C Zhang, A Hilmkil arXiv preprint arXiv:2311.03989, 2023 | 3 | 2023 |
| Perceiving music quality with gans A Hilmkil, C Thomé, A Arpteg arXiv preprint arXiv:2006.06287, 2020 | 3 | 2020 |
| Towards Causal Foundation Model: on Duality between Optimal Balancing and Attention J Zhang, J Jennings, A Hilmkil, N Pawlowski, C Zhang, C Ma Forty-first International Conference on Machine Learning, 0 | 3 | |
| AVID: Adapting Video Diffusion Models to World Models M Rigter, T Gupta, A Hilmkil, C Ma arXiv preprint arXiv:2410.12822, 2024 | 1 | 2024 |
| 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 | 1 | 2024 |
| Pyramid Vector Quantization for LLMs TFA van der Ouderaa, ML Croci, A Hilmkil, J Hensman arXiv preprint arXiv:2410.16926, 2024 | | 2024 |
| Zero-Shot Learning of Causal Models D Mahajan, J Gladrow, A Hilmkil, C Zhang, M Scetbon arXiv preprint arXiv:2410.06128, 2024 | | 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 | | 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 | | 2024 |
| ProxyTune: Hyperparameter tuning through iteratively refined proxies A Hilmkil, W Gong, N Pawlowski, C Zhang ICML 2024 Workshop on Structured Probabilistic Inference {\&} Generative …, 0 | | |
| A Fixed-Point Approach for Causal Generative Modeling M Scetbon, J Jennings, A Hilmkil, C Zhang, C Ma Forty-first International Conference on Machine Learning, 0 | | |
| Towards Machine Learning on Data from Professional Cyclists O Ivarsson, A Hilmkil, M Johansson | | |
