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cs.CV2024
Autoassociative Learning of Structural Representations for Modeling and Classification in Medical Imaging
Zuzanna Buchnajzer, Kacper Dobek, Stanisław Hapke +2
Deep learning architectures based on convolutional neural networks tend to rely on continuous, smooth features. While this characteristics provides significant robustness and prove…
cs.AI2024★ 2 cited
Learning to Solve Abstract Reasoning Problems with Neurosymbolic Program Synthesis and Task Generation
Jakub Bednarek, Krzysztof Krawiec
The ability to think abstractly and reason by analogy is a prerequisite to rapidly adapt to new conditions, tackle newly encountered problems by decomposing them, and synthesize kn…
cs.CV2024★ 2 cited
Disentangling Visual Priors: Unsupervised Learning of Scene Interpretations with Compositional Autoencoder
Krzysztof Krawiec, Antoni Nowinowski
Contemporary deep learning architectures lack principled means for capturing and handling fundamental visual concepts, like objects, shapes, geometric transforms, and other higher-…