Zobrazeno 1 - 10
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pro vyhledávání: '"Å Jensen, A."'
Graph stream summarization refers to the process of processing a continuous stream of edges that form a rapidly evolving graph. The primary challenges in handling graph streams include the impracticality of fully storing the ever-growing datasets and
Externí odkaz:
http://arxiv.org/abs/2412.15516
Autor:
Istas, Mathieu, Jensen, Scott, Yang, Yubo, Holzmann, Markus, Pierleoni, Carlo, Ceperley, David M.
We simulate high-pressure hydrogen in its liquid phase close to molecular dissociation using a machine-learned interatomic potential. The model is trained with density functional theory (DFT) forces and energies, with the Perdew-Burke-Ernzerhof (PBE)
Externí odkaz:
http://arxiv.org/abs/2412.14953
Autor:
Holmes, Andrew, Jensen, Matt, Coffland, Sarah, Shen, Hidemi Mitani, Sizemore, Logan, Bassetti, Seth, Nieva, Brenna, Tebaldi, Claudia, Snyder, Abigail, Hutchinson, Brian
The Global Change Analysis Model (GCAM) simulates complex interactions between the coupled Earth and human systems, providing valuable insights into the co-evolution of land, water, and energy sectors under different future scenarios. Understanding t
Externí odkaz:
http://arxiv.org/abs/2412.08850
Autor:
Rajib, Md Mahadi, Bhattacharya, Dhritiman, Jensen, Christopher J., Chen, Gong, Chowdhury, Fahim F, Sarkar, Shouvik, Liu, Kai, Atulasimha, Jayasimha
Recent progresses in magnetoionics offer exciting potentials to leverage its non-linearity, short-term memory, and energy-efficiency to uniquely advance the field of physical reservoir computing. In this work, we experimentally demonstrate the classi
Externí odkaz:
http://arxiv.org/abs/2412.06964
Mechanistic interpretability aims to understand the inner workings of large neural networks by identifying circuits, or minimal subgraphs within the model that implement algorithms responsible for performing specific tasks. These circuits are typical
Externí odkaz:
http://arxiv.org/abs/2411.16105
Autor:
Chakradeo, Kaustubh, Nielsen, Pernille, Gjerdrum, Lise Mette Rahbek, Hansen, Gry Sahl, Duchêne, David A, Mortensen, Laust H, Jensen, Majken K, Bhatt, Samir
As global life expectancy increases, so does the burden of chronic diseases, yet individuals exhibit considerable variability in the rate at which they age. Identifying biomarkers that distinguish fast from slow ageing is crucial for understanding th
Externí odkaz:
http://arxiv.org/abs/2411.16956
Autor:
Goswami, Shubhang, Jensen, Scott, Yang, Yubo, Holzmann, Markus, Pierleoni, Carlo, Ceperley, David M.
We present results and discuss methods for computing the melting temperature of dense molecular hydrogen using a machine learned model trained on quantum Monte Carlo data. In this newly trained model, we emphasize the importance of accurate total ene
Externí odkaz:
http://arxiv.org/abs/2411.15665
Trajectory representation learning (TRL) maps trajectories to vectors that can then be used for various downstream tasks, including trajectory similarity computation, trajectory classification, and travel-time estimation. However, existing TRL method
Externí odkaz:
http://arxiv.org/abs/2411.15096
Trajectory representation learning (TRL) maps trajectories to vectors that can be used for many downstream tasks. Existing TRL methods use either grid trajectories, capturing movement in free space, or road trajectories, capturing movement in a road
Externí odkaz:
http://arxiv.org/abs/2411.14768
Publikováno v:
EPTCS 412, 2024, pp. 2-18
We study the data-parallel language BUTF, inspired by the Futhark language for array programming. We give a translation of BUTF into a version of the pi-calculus with broadcasting and labeled names. The translation is both complete and sound. Moreove
Externí odkaz:
http://arxiv.org/abs/2411.14579