Adaptive Soft Contrastive Learning
A self-supervised learning method aiming to alleviate the inherent false-negative problem in contrastive learning framework.
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A self-supervised learning method aiming to alleviate the inherent false-negative problem in contrastive learning framework.
A robust and efficient training framework tackling with dataset with noisy labels.
A self-supervised pre-training method with focus on alleviating class collision problem using a cross-context learning scheme.
A CLIP-based visual-language model called DFER-CLIP for in-the-wild dynamic facial expression of emotion recognition.
Leverages the association between parts of speech and specific visual modes of variation to better separate representations of style from content in the CLIP representations
Localized image editing through joint factorization of parts of appearances in pre-trained GANs.
A neural network-based time-series forecasting model for concentrations of an electrochemical reaction.
A method for controlling diversity between clusterings in deep clustering frameworks.
A lightweight AI rerouting decision model that helps to determine whether running weather routing is beneficial. The goal of the model is to help minimize the high computational workload demanded by a commercial weather routing system that performs freque...