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Found 3 papers, 3 papers with code
A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis
Unlike mainstream classifiers that wait until the last fully-connected layer to incorporate class information to make predictions, we investigate a proactive approach, asking each class to search for itself in an image.
Discovering Novel Biological Traits From Images Using Phylogeny-Guided Neural Networks
Discovering evolutionary traits that are heritable across species on the tree of life (also referred to as a phylogenetic tree) is of great interest to biologists to understand how organisms diversify and evolve.
Learning Fractals by Gradient Descent
Fractals are geometric shapes that can display complex and self-similar patterns found in nature (e. g., clouds and plants).
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