Towards Machine Learning on data from Professional Cyclists. - Agrin Hilmkil; Oscar Ivarsson; Moa Johansson; Dan Kuylenstierna; Teun van Erp (CoRR, 2018)

Perceiving Music Quality with GANs. - Agrin Hilmkil; Carl Thomé; Anders Arpteg (CoRR, 2020)

Scaling Federated Learning for Fine-Tuning of Large Language Models. - Agrin Hilmkil; Sebastian Callh; Matteo Barbieri; Leon René Sütfeld; Edvin Listo Zec; Olof Mogren (NLDB, 2021)

SHIBR - The Swedish Historical Birth Records: a semi-annotated dataset. - Abbas Cheddad; Hüseyin Kusetogullari; Agrin Hilmkil; Lena Sundin; Amir Yavariabdi; Aouache Mustapha; Johan Hall (Neural Comput. Appl., 2021)

Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning. - Matthew Ashman; Chao Ma 019; Agrin Hilmkil; Joel Jennings; Cheng Zhang 005 (ICLR, 2023)

Understanding Causality with Large Language Models: Feasibility and Opportunities. - Cheng Zhang 005; Stefan Bauer; Paul Bennett; Jiangfeng Gao; Wenbo Gong 001; Agrin Hilmkil; Joel Jennings; Chao Ma 019; Tom Minka; Nick Pawlowski; James Vaughan (CoRR, 2023)

Learned Causal Method Prediction. - Shantanu Gupta; Cheng Zhang; Agrin Hilmkil (CoRR, 2023)

A Fixed-Point Approach for Causal Generative Modeling. - Meyer Scetbon; Joel Jennings; Agrin Hilmkil; Cheng Zhang 005; Chao Ma 019 (ICML, 2024)

Towards Causal Foundation Model: on Duality between Optimal Balancing and Attention. - Jiaqi Zhang; Joel Jennings; Agrin Hilmkil; Nick Pawlowski; Cheng Zhang 005; Chao Ma 019 (ICML, 2024)

The Essential Role of Causality in Foundation World Models for Embodied AI. - Tarun Gupta 002; Wenbo Gong 001; Chao Ma 019; Nick Pawlowski; Agrin Hilmkil; Meyer Scetbon; Ade Famoti; Ashley Juan Llorens; Jianfeng Gao 001; Stefan Bauer; Danica Kragic; Bernhard Schölkopf; et al. (CoRR, 2024)

FiP: a Fixed-Point Approach for Causal Generative Modeling. - Meyer Scetbon; Joel Jennings; Agrin Hilmkil; Cheng Zhang 005; Chao Ma 019 (CoRR, 2024)

Zero-Shot Learning of Causal Models. - Divyat Mahajan; Jannes Gladrow; Agrin Hilmkil; Cheng Zhang 005; Meyer Scetbon (CoRR, 2024)

AVID: Adapting Video Diffusion Models to World Models. - Marc Rigter; Tarun Gupta 002; Agrin Hilmkil; Chao Ma 019 (CoRR, 2024)

Pyramid Vector Quantization for LLMs. - Tycho F. A. van der Ouderaa; Maximilian L. Croci; Agrin Hilmkil; James Hensman (CoRR, 2024)

Deep End-to-end Causal Inference. - Tomas Geffner; Javier Antorán; Adam Foster 001; Wenbo Gong 001; Chao Ma 019; Emre Kiciman; Amit Sharma 007; Angus Lamb; Martin Kukla; Nick Pawlowski; Agrin Hilmkil; Joel Jennings; et al. (Trans. Mach. Learn. Res., 2024)