Specificity
480 papers with code • 0 benchmarks • 1 datasets
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MACSum
Most implemented papers
Personalizing Dialogue Agents: I have a dog, do you have pets too?
facebookresearch/ParlAI
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ACL 2018
Chit-chat models are known to have several problems: they lack specificity, do not display a consistent personality and are often not very captivating.
MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs
pyaf/DenseNet-MURA-PyTorch
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To evaluate models robustly and to get an estimate of radiologist performance, we collect additional labels from six board-certified Stanford radiologists on the test set, consisting of 207 musculoskeletal studies.
Cellular automata as convolutional neural networks
This motivates our development of a general convolutional multilayer perceptron architecture, which we find can learn the dynamical rules for arbitrary CA when given videos of the CA as training data.
Deep Learning to Improve Breast Cancer Early Detection on Screening Mammography
We also demonstrate that a whole image classifier trained using our end-to-end approach on the DDSM digitized film mammograms can be transferred to INbreast FFDM images using only a subset of the INbreast data for fine-tuning and without further reliance on the availability of lesion annotations.
A Tsetlin Machine with Multigranular Clauses
The recently introduced Tsetlin Machine (TM) has provided competitive pattern recognition accuracy in several benchmarks, however, requires a 3-dimensional hyperparameter search.
POCOVID-Net: Automatic Detection of COVID-19 From a New Lung Ultrasound Imaging Dataset (POCUS)
jannisborn/covid19_pocus_ultrasound
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For detecting COVID-19 in particular, the model performs with a sensitivity of 0. 96, a specificity of 0. 79 and F1-score of 0. 92 in a 5-fold cross validation.
Neural Vector Spaces for Unsupervised Information Retrieval
We propose the Neural Vector Space Model (NVSM), a method that learns representations of documents in an unsupervised manner for news article retrieval.
Predicting Splicing from Primary Sequence with Deep Learning
Illumina/SpliceAI
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A Cell Press journal 2019
The splicing of pre-mRNAs into mature transcripts is remarkable for its precision, but the mechanisms by which the cellular machinery achieves such specificity are incompletely understood.
3D Convolutional Neural Networks for Stalled Brain Capillary Detection
Recent advances in imaging technology enabled generation of high-quality 3D images that can be used to visualize stalled blood vessels.
Locating and Editing Factual Associations in GPT
kmeng01/rome
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To test our hypothesis that these computations correspond to factual association recall, we modify feed-forward weights to update specific factual associations using Rank-One Model Editing (ROME).
