Zobrazeno 1 - 10
of 32 184
pro vyhledávání: '"A. Rickard"'
Autor:
B. Ervens, A. Rickard, B. Aumont, W. P. L. Carter, M. McGillen, A. Mellouki, J. Orlando, B. Picquet-Varrault, P. Seakins, W. R. Stockwell, L. Vereecken, T. J. Wallington
Publikováno v:
Atmospheric Chemistry and Physics, Vol 24, Pp 13317-13339 (2024)
Chemical mechanisms form the core of atmospheric models to describe degradation pathways of pollutants and ultimately inform air quality and climate policymakers and other stakeholders. The accuracy of chemical mechanisms relies on the quality of the
Externí odkaz:
https://doaj.org/article/ae95af7e777f4a2b84076046d2ebfb49
Autor:
Rickard, M. J., Hainich, R., Pauli, D., Hamann, W. -R., Oskinova, L. M., Prinja, R. K., Ramachandran, V., Todt, H., Schösser, E. C., Sander, A. A. C., Zeidler, P.
Publikováno v:
M. Rickard et al. (2024) A149
NGC 346 is a young cluster with numerous hot OB stars. It is part of the Small Magellanic Cloud (SMC), and has an average metallicity that is one-seventh of the Milky Way's. A detailed study of its stellar content provides a unique opportunity to und
Externí odkaz:
http://arxiv.org/abs/2412.07373
When exploring new magnetic materials, the effect of alloying plays a crucial role for numerous properties. By altering the alloy composition, it is possible to tailor, e.g., the Curie temperature ($T_\text{C}$). In this work, $T_\text{C}$ of various
Externí odkaz:
http://arxiv.org/abs/2412.04920
Autor:
Khalighinejad, Ghazal, Scott, Sharon, Liu, Ollie, Anderson, Kelly L., Stureborg, Rickard, Tyagi, Aman, Dhingra, Bhuwan
Multimodal information extraction (MIE) is crucial for scientific literature, where valuable data is often spread across text, figures, and tables. In materials science, extracting structured information from research articles can accelerate the disc
Externí odkaz:
http://arxiv.org/abs/2410.20494
Path planners that can interpret free-form natural language instructions hold promise to automate a wide range of robotics applications. These planners simplify user interactions and enable intuitive control over complex semi-autonomous systems. Whil
Externí odkaz:
http://arxiv.org/abs/2409.06859
Scaling laws dictate that the performance of AI models is proportional to the amount of available data. Data augmentation is a promising solution to expanding the dataset size. Traditional approaches focused on augmentation using rotation, translatio
Externí odkaz:
http://arxiv.org/abs/2409.00547
Autor:
Bulancea-Lindvall, Oscar, Davidsson, Joel, Ivanov, Ivan G., Gali, Adam, Ivády, Viktor, Armiento, Rickard, Abrikosov, Igor A.
Publikováno v:
Phys. Rev. Applied 22, 034056 (2024)
Defects in semiconductors have in recent years been revealed to have interesting properties in the venture towards quantum technologies. In this regard, silicon carbide has shown great promise as a host for quantum defects. In particular, the ultra-b
Externí odkaz:
http://arxiv.org/abs/2408.06823
The advent of machine learning in materials science opens the way for exciting and ambitious simulations of large systems and long time scales with the accuracy of ab-initio calculations. Recently, several pre-trained universal machine learned intera
Externí odkaz:
http://arxiv.org/abs/2406.17499
One approach for increasing the efficiency of randomized trials is the use of "external controls" -- individuals who received the control treatment in the trial during routine practice or in prior experimental studies. Existing external control metho
Externí odkaz:
http://arxiv.org/abs/2406.17971
Autor:
Brüel-Gabrielsson, Rickard, Zhu, Jiacheng, Bhardwaj, Onkar, Choshen, Leshem, Greenewald, Kristjan, Yurochkin, Mikhail, Solomon, Justin
Fine-tuning large language models (LLMs) with low-rank adaptations (LoRAs) has become common practice, often yielding numerous copies of the same LLM differing only in their LoRA updates. This paradigm presents challenges for systems that serve real-
Externí odkaz:
http://arxiv.org/abs/2407.00066