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31 to 40 of 294 Results
Apr 16, 2020 - AWI Experimental Economics
Kops, Christopher; Pasichnichenko, Illia, 2020, "A Test of Information Aversion", https://doi.org/10.11588/data/G0RNAZ, heiDATA, V1, UNF:6:GkvwqL6qHXH4RRvkp1xJWA== [fileUNF]
The standard Bayesian model implies that information can never have a negative value. We put this implication to the proof. Our paper provides the first test of the value (positive or negative) of information under uncertainty. We show that the ``Bayesian implication'' stands in...
Apr 6, 2020 - Anders Group
Tobias Roider; Julian Seufert; Alexey Uvarovskii; Felix Frauhammer; Marie Bordas; Nima Abedpour; Marta Stolarczyk; Jan-Philipp Mallm; Sophie A. Herbst; Peter-Martin Bruch; Hyatt Balke-Want; Michael Hundemer; Karsten Rippe; Benjamin Goeppert; Martina Seiffert; Benedikt Brors; Gunhild Mechtersheimer; Thorsten Zenz; Martin Peifer; Björn Chapuy; Matthias Schlesner; Carsten Müller-Tidow; Stefan Fröhling; Wolfgang Huber; Simon Anders; Sascha Dietrich, 2020, "Dissecting intratumor heterogeneity of nodal B cell lymphomas at transcriptional, genetic, and drug response levels", https://doi.org/10.11588/data/VRJUNV, heiDATA, V1, UNF:6:AlKw3YwYZ82Ty5CxnC4D5w== [fileUNF]
Tumour heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is known to affect the efficacy of cancer therapy, most personalized treatment approaches do not account for intratumor heterogeneity. We addresse...
Anders Group(Center for Molecular Biology of Heidelberg University (ZMBH))
Apr 6, 2020
Data publications from the Anders Group at the Center for Molecular Biology of Heidelberg University (ZMBH)
Apr 2, 2020 - Synthetic Quantum Systems (SynQS)
Hesse, Alexander; Köster, Kerim; Steiner, Jakob; Michl, Julia; Vorobyov, Vadim; Dasari, Durga; Wrachtrup, Jörg; Jendrzejewski, Fred, 2020, "Direct control of high magnetic fields for cold atom experiments based on NV centers [Dataset]", https://doi.org/10.11588/data/W60KUN, heiDATA, V2, UNF:6:3I/nRXdQ66s4MU0XvXd49g== [fileUNF]
In atomic physics experiments, magnetic fields allow to control the interactions between atoms, eg. near Feshbach resonances, or by employing spin changing collisions. The magnetic field control is typically performed indirectly, by stabilizing the current of Helmholtz coils prod...
Synthetic Quantum Systems (SynQS)(Kirchhoff Institute for Physics, Heidelberg University)
Apr 2, 2020
Open Research Data from the Synthetic Quantum Systems (SynQS) Group at Heidelberg University's Kirchhoff Institute for Physics.
Mar 26, 2020 - Empirical Linguistics and Computational Language Modeling (LiMo)
Rehbein, Ines; Ruppenhofer, Josef; Do, Bich-Ngoc, 2020, "tweeDe", https://doi.org/10.11588/data/S90S35, heiDATA, V1
A German UD Twitter treebank, with >12,000 tokens from 519 tweets, annotated in the Universal Dependencies framework
Mar 26, 2020 - Empirical Linguistics and Computational Language Modeling (LiMo)
Rehbein, Ines; Ruppenhofer, Josef; Zimmermann, Victor, 2020, "Pre-trained POS tagging models for German social media", https://doi.org/10.11588/data/W3JBV4, heiDATA, V1
Pre-trained POS tagging models for the HunPos tagger (Halácsy et al. 2007) the biLSTM-char-CRF tagger (Reimers & Gurevych 2017) Online-Flors (Yin et al. 2015). References: Halácsy, P., Kornai, A., and Oravecz, C. (2007). HunPos: An open source trigram tagger. In Proceedings of th...
Mar 26, 2020 - Empirical Linguistics and Computational Language Modeling (LiMo)
Rehbein, Ines; Ruppenhofer, Josef; Zimmermann, Victor, 2020, "A harmonised testsuite for social media POS tagging (DE)", https://doi.org/10.11588/data/KXLMHN, heiDATA, V1
A harmonised POS testsuite of web data, CMC and Twitter microtext, with word forms and STTS pos tags (+ some additional CMC-specific tags). UD pos tags have been automatically converted, based on the STTS pos tags. The data does not contain (manually corrected) lemma information....
Mar 26, 2020 - Empirical Linguistics and Computational Language Modeling (LiMo)
Rehbein, Ines; Steen, Julius; Do, Bich-Ngoc; Frank, Anette, 2020, "Converter for content-to-head style syntactic dependencies", https://doi.org/10.11588/data/HE3BAZ, heiDATA, V1
A set of Python scripts that convert function-head style encodings in dependency treebanks in a content-head style encoding (as used in the UD treebanks) and vice versa (for adpositions, copula and coordination). For more information, see (Rehbein, Steen, Do & Frank 2017).
Mar 26, 2020 - Empirical Linguistics and Computational Language Modeling (LiMo)
Rehbein, Ines; Ruppenhofer, Josef, 2020, "MACE-AL-TREE", https://doi.org/10.11588/data/THPEBR, heiDATA, V1
An method for detecting noise in automatically annotated dependency parse trees, combining MACE (Hovy et al. 2013) with Active Learning.
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