Search Results for author:
Found 5 papers, 2 papers with code
CONTaiNER: Few-Shot Named Entity Recognition via Contrastive Learning
Named Entity Recognition (NER) in Few-Shot setting is imperative for entity tagging in low resource domains.
Ranked #2 on
Few-shot NER
on Few-NERD (INTRA)
(using extra training data)
A Survey on Deep Learning Based Point-Of-Interest (POI) Recommendations
Our work categorizes and critically analyzes the recent POI recommendation works based on different deep learning paradigms and other relevant features.
BayesBeat: A Bayesian Deep Learning Approach for Atrial Fibrillation Detection from Noisy Photoplethysmography Data
The increasing popularity of smartwatches as affordable and longitudinal monitoring devices enables us to capture photoplethysmography (PPG) sensor data for detecting Atrial Fibrillation (AF) in real-time.
Boosting House Price Predictions using Geo-Spatial Network Embedding
Extensive experiments with a large number of regression techniques show that the embeddings produced by our proposed GSNE technique consistently and significantly improve the performance of the house price prediction task regardless of the downstream regression model.
CCCNet: An Attention Based Deep Learning Framework for Categorized Crowd Counting
In this paper, we introduce a new variant of crowd counting problem, namely "Categorized Crowd Counting", that counts the number of people sitting and standing in a given image.
