Zobrazeno 1 - 10
of 25 547
pro vyhledávání: '"A. Huth"'
Publikováno v:
Biogeosciences, Vol 19, Pp 4929-4944 (2022)
Describing the heterogeneous structure of forests is often challenging. One possibility is to analyze forest biomass in different plots and to derive plot-based frequency distributions. However, these frequency distributions depend on the plot size a
Externí odkaz:
https://doaj.org/article/4891c09807a34aabbc9cb6511ac5ec3f
Publikováno v:
Biogeosciences, Vol 19, Pp 1891-1911 (2022)
Disturbances, such as extreme weather events, fires, floods, and biotic agents, can have strong impacts on the dynamics and structures of tropical forests. In the future, the intensity of disturbances will likely further increase, which may have more
Externí odkaz:
https://doaj.org/article/b50c4c15349f4beab2dab2e7e8509531
Autor:
J. Pacheco-Labrador, U. Weber, X. Ma, M. D. Mahecha, N. Carvalhais, C. Wirth, A. Huth, F. J. Bohn, G. Kraemer, U. Heiden, FunDivEUROPE members, M. Migliavacca
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVI-1-W1-2021, Pp 49-55 (2022)
Tackling the accelerated human-induced biodiversity loss requires tools able to map biodiversity and its changes globally. Remote sensing (RS) offers unique capabilities of characterizing Earth surfaces; therefore, it could map plant biodiversity con
Externí odkaz:
https://doaj.org/article/b9c9bb5df1ff444bb5762ab3d3120231
Autor:
Pink, Mathis, Vo, Vy A., Wu, Qinyuan, Mu, Jianing, Turek, Javier S., Hasson, Uri, Norman, Kenneth A., Michelmann, Sebastian, Huth, Alexander, Toneva, Mariya
Current LLM benchmarks focus on evaluating models' memory of facts and semantic relations, primarily assessing semantic aspects of long-term memory. However, in humans, long-term memory also includes episodic memory, which links memories to their con
Externí odkaz:
http://arxiv.org/abs/2410.08133
A generative framework to bridge data-driven models and scientific theories in language neuroscience
Autor:
Antonello, Richard, Singh, Chandan, Jain, Shailee, Hsu, Aliyah, Gao, Jianfeng, Yu, Bin, Huth, Alexander
Representations from large language models are highly effective at predicting BOLD fMRI responses to language stimuli. However, these representations are largely opaque: it is unclear what features of the language stimulus drive the response in each
Externí odkaz:
http://arxiv.org/abs/2410.00812
Autor:
Anibal, James, Gunkel, Jasmine, Huth, Hannah, Nguyen, Hang, Awan, Shaheen, Bensoussan, Yael, Wood, Bradford
Clinical artificial intelligence (AI) methods have been proposed for predicting social behaviors which could be reasonably understood from patient-reported data. This raises ethical concerns about respect, privacy, and patient awareness/control over
Externí odkaz:
http://arxiv.org/abs/2408.07896
Publikováno v:
Journal of Advances in Modeling Earth Systems, Vol 14, Iss 3, Pp n/a-n/a (2022)
Abstract Large tabular icebergs account for the majority of ice mass calved from Antarctic ice shelves, but are omitted from climate models. Specifically, these models do not account for iceberg breakup and as a result, modeled large icebergs could d
Externí odkaz:
https://doaj.org/article/cb630366f95c4f75a56fa519d20e16c1
Autor:
Wennlöf, Håkan, Dannheim, Dominik, Viera, Manuel Del Rio, Dort, Katharina, Eckstein, Doris, Feindt, Finn, Gregor, Ingrid-Maria, Huth, Lennart, Lachnit, Stephan, Mendes, Larissa, Rastorguev, Daniil, Daza, Sara Ruiz, Schütze, Paul, Simancas, Adriana, Snoeys, Walter, Spannagel, Simon, Stanitzki, Marcel, Tomal, Alessandra, Velyka, Anastasiia, Vignola, Gianpiero
The optimisation of the sensitive region of CMOS sensors with complex non-uniform electric fields requires precise simulations, and this can be achieved by a combination of electrostatic field simulations and Monte Carlo methods. This paper presents
Externí odkaz:
http://arxiv.org/abs/2408.00027
Autor:
Benara, Vinamra, Singh, Chandan, Morris, John X., Antonello, Richard, Stoica, Ion, Huth, Alexander G., Gao, Jianfeng
Large language models (LLMs) have rapidly improved text embeddings for a growing array of natural-language processing tasks. However, their opaqueness and proliferation into scientific domains such as neuroscience have created a growing need for inte
Externí odkaz:
http://arxiv.org/abs/2405.16714
Brain-computer interfaces have promising medical and scientific applications for aiding speech and studying the brain. In this work, we propose an information-based evaluation metric for brain-to-text decoders. Using this metric, we examine two metho
Externí odkaz:
http://arxiv.org/abs/2405.14055