Agrin Hilmkil

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 12

Top Topics

Bargaining Solution

Causal Reasoning

Top Venues

Neural Comput. Appl.

Publications

Meyer Scetbon, Joel Jennings, Agrin Hilmkil, Cheng Zhang, Chao Ma
FiP: a Fixed-Point Approach for Causal Generative Modeling. CoRR (2024)
Tarun Gupta, Wenbo Gong, Chao Ma, Nick Pawlowski, Agrin Hilmkil, Meyer Scetbon, Ade Famoti, Ashley Juan Llorens, Jianfeng Gao, Stefan Bauer, Danica Kragic, Bernhard Schölkopf, Cheng Zhang
The Essential Role of Causality in Foundation World Models for Embodied AI. CoRR (2024)
Tomas Geffner, Javier Antorán, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Agrin Hilmkil, Joel Jennings, Meyer Scetbon, Miltiadis Allamanis, Cheng Zhang
Deep End-to-end Causal Inference. Trans. Mach. Learn. Res. 2024 (2024)
Matthew Ashman, Chao Ma, Agrin Hilmkil, Joel Jennings, Cheng Zhang
Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning. CoRR (2023)
Matthew Ashman, Chao Ma, Agrin Hilmkil, Joel Jennings, Cheng Zhang
Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning. ICLR (2023)
Cheng Zhang, Stefan Bauer, Paul Bennett, Jiangfeng Gao, Wenbo Gong, Agrin Hilmkil, Joel Jennings, Chao Ma, Tom Minka, Nick Pawlowski, James Vaughan
Understanding Causality with Large Language Models: Feasibility and Opportunities. CoRR (2023)
Shantanu Gupta, Cheng Zhang, Agrin Hilmkil
Learned Causal Method Prediction. CoRR (2023)
Abbas Cheddad, Hüseyin Kusetogullari, Agrin Hilmkil, Lena Sundin, Amir Yavariabdi, Mustapha Aouache, Johan Hall
SHIBR - The Swedish Historical Birth Records: a semi-annotated dataset. Neural Comput. Appl. 33 (22) (2021)
Agrin Hilmkil, Sebastian Callh, Matteo Barbieri, Leon René Sütfeld, Edvin Listo Zec, Olof Mogren
Scaling Federated Learning for Fine-Tuning of Large Language Models. NLDB (2021)
Agrin Hilmkil, Sebastian Callh, Matteo Barbieri, Leon René Sütfeld, Edvin Listo Zec, Olof Mogren
Scaling Federated Learning for Fine-tuning of Large Language Models. CoRR (2021)
Agrin Hilmkil, Carl Thomé, Anders Arpteg
Perceiving Music Quality with GANs. CoRR (2020)
Agrin Hilmkil, Oscar Ivarsson, Moa Johansson, Dan Kuylenstierna, Teun van Erp
Towards Machine Learning on data from Professional Cyclists. CoRR (2018)