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Found 11 papers, 3 papers with code
Unsupervised hard Negative Augmentation for contrastive learning
We present Unsupervised hard Negative Augmentation (UNA), a method that generates synthetic negative instances based on the term frequency-inverse document frequency (TF-IDF) retrieval model.
E-NER -- An Annotated Named Entity Recognition Corpus of Legal Text
Nevertheless, there are publicly available NER data sets for general English.
Estimating the Uncertainty of Neural Network Forecasts for Influenza Prevalence Using Web Search Activity
In this paper, we demonstrate how Bayesian Neural Networks (BNNs) can be used to both provide a forecast and a corresponding uncertainty without significant loss in forecasting accuracy compared to traditional NNs.
Providing early indication of regional anomalies in COVID19 case counts in England using search engine queries
Our analysis shows that searches for "fever" and "cough" were the most correlated with future case counts, with searches preceding case counts by 16-17 days.
Tracking COVID-19 using online search
Furthermore, we analyse the time series of online search queries in relation to confirmed COVID-19 cases data jointly across multiple countries, uncovering interesting patterns.
Social and Information Networks
Changes in Psycholinguistic Attributes of Social Media Users Before, During, and After Self-Reported Influenza Symptoms
Previous research has linked psychological and social variables to physical health.
Flu Detector: Estimating influenza-like illness rates from online user-generated content
We provide a brief technical description of an online platform for disease monitoring, titled as the Flu Detector (fludetector. cs. ucl. ac. uk).
