Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Mario Michael Krell"'
Autor:
Sirko eStraube, Mario Michael Krell
Publikováno v:
Frontiers in Computational Neuroscience, Vol 8 (2014)
In everyday life, humans and animals often have to base decisions on infrequent relevant stimuli with respect to frequent irrelevant ones. When research in neuroscience mimics this situation, the effect of this imbalance in stimulus classes on perfor
Externí odkaz:
https://doaj.org/article/9980f703609e462b92625aa4bcee2325
Autor:
Mario Michael Krell, Sirko eStraube, Anett eSeeland, Hendrik eWöhrle, Johannes eTeiwes, Jan Hendrik Metzen, Elsa Andrea Kirchner, Frank eKirchner
Publikováno v:
Frontiers in Neuroinformatics, Vol 7 (2013)
In neuroscience large amounts of data are recorded to provide insights into cerebral information processing and function. The successful extraction of the relevant signals becomes more and more challenging due to increasing complexities in acquisitio
Externí odkaz:
https://doaj.org/article/0ffdd9f039254bf68f1a2798ee780a99
Autor:
Elsa Andrea Kirchner, Su Kyoung Kim, Sirko Straube, Anett Seeland, Hendrik Wöhrle, Mario Michael Krell, Marc Tabie, Manfred Fahle
Publikováno v:
PLoS ONE, Vol 8, Iss 12, p e81732 (2013)
The ability of today's robots to autonomously support humans in their daily activities is still limited. To improve this, predictive human-machine interfaces (HMIs) can be applied to better support future interaction between human and machine. To inf
Externí odkaz:
https://doaj.org/article/394f7c720b0b4c4381bd7ab8b6baeeef
Objective: Classifier transfers usually come with dataset shifts. To overcome them, online strategies have to be applied. For practical applications, limitations in the computational resources for the adaptation of batch learning algorithms, like the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e52ff3982435bd5a2dd9d12443357a7f
Publikováno v:
2020 International Conference on Rebooting Computing (ICRC)
ICRC
ICRC
Developing models of natural phenomena by capturing their underlying complex interactions is a core tenet of various scientific disciplines. These models are useful as simulators and can help in understanding the natural processes being studied. One
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::02c5ecb424d523e5af6cda466759719f
Epidemiology models are central to understanding and controlling large-scale pandemics. Several epidemiology models require simulation-based inference such as Approximate Bayesian Computation (ABC) to fit their parameters to observations. ABC inferen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f9d2ffabce9c28300b3bbf503838b2c
Autor:
Sirko Straube, Mario Michael Krell
Publikováno v:
Advances in Data Analysis and Classification. 11:415-439
Data processing often transforms a complex signal using a set of different preprocessing algorithms to a single value as the outcome of a final decision function. Still, it is challenging to understand and visualize the interplay between the algorith
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8321a6763a29ac7c55b24d1f3d9458fa
https://doi.org/10.1007/s11634-015-0229-3
https://doi.org/10.1007/s11634-015-0229-3
Memorization is worst-case generalization. Based on MacKay's information theoretic model of supervised machine learning, this article discusses how to practically estimate the maximum size of a neural network given a training data set. First, we pres
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd11bf75dd87a09d42a26e4bd2d9e395
https://doi.org/10.2172/1476219
https://doi.org/10.2172/1476219
Multi-context model learning is crucial for marine robotics where several factors can cause disturbances to the system's dynamics. This work addresses the problem of identifying multiple contexts of an AUV model. We build a simulation model of the ro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cdcf2180818561cb509b2471658d4e7c
http://arxiv.org/abs/1809.06179
http://arxiv.org/abs/1809.06179
Autor:
Frank Kirchner, Sirko Straube, Elsa Andrea Kirchner, Hendrik Woehrle, Su Kyoung Kim, Mario Michael Krell
Publikováno v:
IEEE Transactions on Biomedical Engineering. 62:1696-1705
Goal: Current brain–computer interfaces (BCIs) are usually based on various, often supervised, signal processing methods. The disadvantage of supervised methods is the requirement to calibrate them with recently acquired subject-specific training d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db5adbb2811f2eb3207639ef86a07f81
https://doi.org/10.1109/tbme.2015.2402252
https://doi.org/10.1109/tbme.2015.2402252