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heiDATA is an institutional repository for research data of Heidelberg University. It is managed by the Competence Centre for Research Data, a joint institution of the University Library and the Computing Centre. If you are interested in publishing your data here, please see our author instructions and get in touch with us.
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31 to 40 of 233 Results
May 28, 2019 - KnopLab
Buchmuller, Benjamin C; Herbst, Konrad; Meurer, Matthias; Kirrmaier, Daniel; Sass, Ehud; Levy, Emmanuel D; Knop, Michael, 2019, "Pooled clone collections by multiplexed CRISPR-Cas12a-assisted gene tagging in yeast [Dataset]", https://doi.org/10.11588/data/L45TRX, heiDATA, V2
Data accompanying the paper "Pooled clone collections by multiplexed CRISPR-Cas12a-assisted gene tagging in yeast" by Buchmuller and Herbst et al, 2019, Nat Communications. This contains raw NGS data for all genotyping analysis in the publication as well as the source code of the...
May 27, 2019 - AWI Experimental Economics
Trautmann, Stefan T.; Kuilen, Gijs van de, 2014, "Belief Elicitation: A Horse Race among Truth Serums [Dataset]", https://doi.org/10.11588/data/10004, heiDATA, V3, UNF:5:rdLqOxsqtpO3QKanCTJFPw== [fileUNF]
We pit non-incentivized introspection against five revealed preference mechanisms (“truth serums”) in the elicitation of beliefs in a simple two-player game. We measure the additivity, the predictive power for own behaviour, and the accuracy of each method. Beliefs from incentivi...
May 21, 2019 - TS-CCEES
Kreyenberg, Philipp J.; Bauser, Hannes H.; Roth, Kurt, 2019, "Velocity Field Estimation on Density-Driven Solute Transport With a Convolutional Neural Network [Dataset]", https://doi.org/10.11588/data/7NEEKF, heiDATA, V1
This data set accompanies the manuscript ‘Velocity Field Estimation on Density-Driven Solute Transport With a Convolutional Neural Network’. Concentration fields are stored as portable pixel maps (.ppm) and flow fields are stored in the Middlebury .flo file format (http://vision....
May 9, 2019 - Heidelberg University Language and Cognition Lab
Stutterheim, Christiane von; Gerwien, Johannes; Bouhaous, Abbassia; Carroll, Mary; Lambert, Monique, 2019, "What makes up a reportable event in a language? Motion events as an important test domain in linguistic typology [Dataset]", https://doi.org/10.11588/data/CLNRAU, heiDATA, V1
Numerous cross-linguistic studies on motion events have been carried out in investigating the scope of the two-fold typology path versus manner (Talmy 1985; 2000) and its possible implications. This typological contrast is too narrow as it stands, however, to account for the dive...
May 9, 2019
Data publications of the Heidelberg University Language and Cognition Lab.
Feb 13, 2019 - TS-CCEES
Berg, Daniel; Hannes H. Bauser; Kurt Roth, 2019, "Covariance resampling for particle filter -- state and parameter estimation for soil hydrology [dataset]", https://doi.org/10.11588/data/MFU6EV, heiDATA, V1
This repository contains the data for the paper 'Covariance resampling for particle filter -- state and parameter estimation for soil hydrology'. All plots contained in the paper can be reproduced using this data.
TS-CCEES(Heidelberg University - Institute of Environmental Physics)
Feb 13, 2019
Data publications of the research group "Terrestrial Systems & Chaotic, Complex, and Evolving Environmental Systems (TS-CCEES)" at the Institute of Environmental Physics at Heidelberg University.
Feb 7, 2019 - SFB 933 Materiale Textkulturen - Teilprojekt A01
Bigi, Francesca, 2019, "Late Antique Statue Bases of Lepcis Magna", https://doi.org/10.11588/data/GLQG7Z, heiDATA, V1, UNF:6:l+7CBMzSs5jxKnIUmRfx8Q== [fileUNF]
Interactive and searchable map of the city of Lepcis Magna, displaying the geographical distribution within the city scape of the late antique honorary and building inscriptions. When translating a multi-faceted and multi-layered reality such as that of late antique Lepcis into a...
Feb 7, 2019SFB 933: Materiale Textkulturen
Datenpublikationen des Teilprojekts A01 des SFB 933: Materiale Textkulturen.
Feb 6, 2019 - AIPHES
Heinzerling, Benjamin, 2019, "BPEmb: Pre-trained Subword Embeddings in 275 Languages (LREC 2018)", https://doi.org/10.11588/data/V9CXPR, heiDATA, V1
BPEmb is a collection of pre-trained subword unit embeddings in 275 languages, based on Byte-Pair Encoding (BPE). In an evaluation using fine-grained entity typing as testbed, BPEmb performs competitively, and for some languages better than alternative subword approaches, while r...
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