Agrin Hilmkil - RankMe

18 papers A* 3C 1Journal 14

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Amortized Inference of Causal Models via Conditional Fixed-Point Iterations. Trans. Mach. Learn. Res. Divyat Mahajan, Jannes Gladrow, Agrin Hilmkil, Cheng Zhang, Meyer Scetbon
2024	A*	`conf`	A Fixed-Point Approach for Causal Generative Modeling. ICML Meyer Scetbon, Joel Jennings, Agrin Hilmkil, Cheng Zhang, Chao Ma
2024	J	`jnl`	AVID: Adapting Video Diffusion Models to World Models. CoRR Marc Rigter, Tarun Gupta, Agrin Hilmkil, Chao Ma
2024	J	`jnl`	Deep End-to-end Causal Inference. Trans. Mach. Learn. Res. 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
2024	J	`jnl`	FiP: a Fixed-Point Approach for Causal Generative Modeling. CoRR Meyer Scetbon, Joel Jennings, Agrin Hilmkil, Cheng Zhang, Chao Ma
2024	J	`jnl`	Pyramid Vector Quantization for LLMs. CoRR Tycho F. A. van der Ouderaa, Maximilian L. Croci, Agrin Hilmkil, James Hensman
2024	J	`jnl`	The Essential Role of Causality in Foundation World Models for Embodied AI. CoRR 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
2024	A*	`conf`	Towards Causal Foundation Model: on Duality between Optimal Balancing and Attention. ICML Jiaqi Zhang, Joel Jennings, Agrin Hilmkil, Nick Pawlowski, Cheng Zhang, Chao Ma
2024	J	`jnl`	Zero-Shot Learning of Causal Models. CoRR Divyat Mahajan, Jannes Gladrow, Agrin Hilmkil, Cheng Zhang, Meyer Scetbon
2023	A*	`conf`	Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning. ICLR Matthew Ashman, Chao Ma, Agrin Hilmkil, Joel Jennings, Cheng Zhang
2023	J	`jnl`	Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning. CoRR Matthew Ashman, Chao Ma, Agrin Hilmkil, Joel Jennings, Cheng Zhang
2023	J	`jnl`	Learned Causal Method Prediction. CoRR Shantanu Gupta, Cheng Zhang, Agrin Hilmkil
2023	J	`jnl`	Understanding Causality with Large Language Models: Feasibility and Opportunities. CoRR Cheng Zhang, Stefan Bauer, Paul Bennett, Jiangfeng Gao, Wenbo Gong, Agrin Hilmkil, Joel Jennings, Chao Ma, Tom Minka, Nick Pawlowski, James Vaughan
2021	J	`jnl`	SHIBR - The Swedish Historical Birth Records: a semi-annotated dataset. Neural Comput. Appl. Abbas Cheddad, Hüseyin Kusetogullari, Agrin Hilmkil, Lena Sundin, Amir Yavariabdi, Aouache Mustapha, Johan Hall
2021	C	`conf`	Scaling Federated Learning for Fine-Tuning of Large Language Models. NLDB Agrin Hilmkil, Sebastian Callh, Matteo Barbieri, Leon René Sütfeld, Edvin Listo Zec, Olof Mogren
2021	J	`jnl`	Scaling Federated Learning for Fine-tuning of Large Language Models. CoRR Agrin Hilmkil, Sebastian Callh, Matteo Barbieri, Leon René Sütfeld, Edvin Listo Zec, Olof Mogren
2020	J	`jnl`	Perceiving Music Quality with GANs. CoRR Agrin Hilmkil, Carl Thomé, Anders Arpteg
2018	J	`jnl`	Towards Machine Learning on data from Professional Cyclists. CoRR Agrin Hilmkil, Oscar Ivarsson, Moa Johansson, Dan Kuylenstierna, Teun van Erp