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12/20/2022
Temporal Output Discrepancy for Loss Estimation-based Active Learning
While deep learning succeeds in a wide range of tasks, it highly depends...
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05/26/2022
Deep Active Learning with Noise Stability
Uncertainty estimation for unlabeled data is crucial to active learning....
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12/10/2021
Boosting Active Learning via Improving Test Performance
Central to active learning (AL) is what data should be selected for anno...
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07/29/2021
Semi-Supervised Active Learning with Temporal Output Discrepancy
While deep learning succeeds in a wide range of tasks, it highly depends...
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11/18/2020
An Evaluation of novel method of Ill-Posed Problem for the Black-Scholes Equation solution
It was proposed by Klibanov a new empirical mathematical method to work ...
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03/17/2020
Parameter-Free Style Projection for Arbitrary Style Transfer
Arbitrary image style transfer is a challenging task which aims to styli...
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09/08/2018
Instance-based Deep Transfer Learning
Deep transfer learning has acquired significant research interest. It ma...
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09/01/2018
Data Dropout: Optimizing Training Data for Convolutional Neural Networks
Deep learning models learn to fit training data while they are highly ex...
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08/14/2017