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Found 4 papers, 1 papers with code
Comprehensive OOD Detection Improvements
As machine learning becomes increasingly prevalent in impactful decisions, recognizing when inference data is outside the model's expected input distribution is paramount for giving context to predictions.
Dimensionality Reduction
Out of Distribution (OOD) Detection
A Novel Explanation Against Linear Neural Networks
However, a novel explanation we propose in this paper for the impracticality of neural networks without activation functions, or linear neural networks, is that they actually reduce both training and testing performance.
Mitigating Negative Transfer in Multi-Task Learning with Exponential Moving Average Loss Weighting Strategies
Multi-Task Learning (MTL) is a growing subject of interest in deep learning, due to its ability to train models more efficiently on multiple tasks compared to using a group of conventional single-task models.
Classification of Abnormal Hand Movement for Aiding in Autism Detection: Machine Learning Study
This work aims to demonstrate the feasibility of deep learning technologies for detecting hand flapping from unstructured home videos as a first step towards validating whether models and digital technologies can be leveraged to aid with autism diagnoses.
