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ShareScore release 0.9.0
Dataset results
6 results for “language representation models”
Representations of language in a model of visually grounded speech signal: Data
<p>The set of datafiles to reproduce results from:</p> <ul> <li>Chrupała, G., Gelderloos, L., & Alishahi, A. (2017). Representations of language in a model of visually grounded speech signal. ACL. arXiv preprint: https://arxiv.org/abs/1702.01991</li> </ul>
Gene-language models are whole genome representation learners
<p>The language of genetic code embodies a complex grammar and rich syntax of interacting molecular elements. Recent advances in self-supervision and feature learning suggest that statistical learning techniques can identify high-quality quantitative representations from inherent semantic structure. We present a gene-based language model that generates whole-genome vector representations from a population of 16 disease-causing bacterial species by leveraging natural contrastive characteristics between individuals. To achieve this, we developed a set-based learning objective, AB learning, that compares the annotated gene content of two population subsets for use in optimization. Using this foundational objective, we trained a Transformer model to backpropagate information into dense genome vector representations. The resulting bacterial representations, or embeddings, captured important population structure characteristics, like delineations across serotypes and host specificity preferences. Their vector quantities encoded the relevant functional information necessary to achieve state-of-the-art genomic supervised prediction accuracy in 11 out of 12 antibiotic resistance phenotypes.</p>
Gene-language models are whole genome representation learners
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Biomedical ELECTRA based deep language representation models for biomedical text mining.
<p>The gzipped tar file contains two biomedical language representation models based on ELECTRA (Clark et al., 2020) deep transformers architecture to be used for down-stream biomedical text mining tasks. </p> <p>Bio-ELECTRA is pre-trained from scratch on PubMed abstracts for 1.8 million steps. Bio-ELECTRA++ is the further pre-trained version of Bio-ELECTRA trained on a corpus of open access full papers from PubMed.</p>
Data for: Can language representation models think in bets?
<p>The dataset contains three files: *Item_Sets.xlsx*, *Value_Questions.xlsx*, and *Bet_Questions.xlsx*. Each of the three files corresponds to each of the three benchmarks in the manuscript currently under submission to Royal Society Open Science and is also available as a preprint: <a href="https://arxiv.org/abs/2210.07519">https://arxiv.org/abs/2210.07519</a>.</p> <p>The items in Item_Sets.xlsx is used to create the other two files. Value_Questions.xlsx is used in RQ1, and Bet_Questions.xlsx is used in both RQ2 and RQ3.</p>
Data for: Can language representation models think in bets?
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ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.