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Found 10 papers, 4 papers with code
Uncertainty Estimation of Transformer Predictions for Misclassification Detection
Uncertainty estimation (UE) of model predictions is a crucial step for a variety of tasks such as active learning, misclassification detection, adversarial attack detection, out-of-distribution detection, etc.
Graph-Based Retriever Captures the Long Tail of Biomedical Knowledge
We introduce a novel information-retrieval method that leverages a knowledge graph to downsample these clusters and mitigate the information overload problem.
SensorSCAN: Self-Supervised Learning and Deep Clustering for Fault Diagnosis in Chemical Processes
However, manual annotation of large amounts of data can be difficult in industrial settings.
Anomaly segmentation model for defects detection in electroluminescence images of heterojunction solar cells
The model was also tested on the open ELPV dataset and demonstrates stable performance with accuracy 94. 6% and F1 score 91. 1%.
New drugs and stock market: how to predict pharma market reaction to clinical trial announcements
The first factor is the drug portfolio size of the company, indicating the greater susceptibility to an announcement in the case of small drug diversification.
Eco2AI: carbon emissions tracking of machine learning models as the first step towards sustainable AI
The size and complexity of deep neural networks continue to grow exponentially, significantly increasing energy consumption for training and inference by these models.
Towards Computationally Feasible Deep Active Learning
Active learning (AL) is a prominent technique for reducing the annotation effort required for training machine learning models.
Project Achoo: A Practical Model and Application for COVID-19 Detection from Recordings of Breath, Voice, and Cough
The COVID-19 pandemic created a significant interest and demand for infection detection and monitoring solutions.
Kernel classification of connectomes based on earth mover's distance between graph spectra
In this paper, we tackle a problem of predicting phenotypes from structural connectomes.
Learning Alternative Name Spellings
Name matching is a key component of systems for entity resolution or record linkage.
