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Found 3 papers, 1 papers with code
Learning Neural Hamiltonian Dynamics: A Methodological Overview
The past few years have witnessed an increased interest in learning Hamiltonian dynamics in deep learning frameworks.
Explaining Point Processes by Learning Interpretable Temporal Logic Rules
We propose a principled method to learn a set of human-readable logic rules to explain temporal point processes.
Perception Improvement for Free: Exploring Imperceptible Black-box Adversarial Attacks on Image Classification
White-box adversarial attacks can fool neural networks with small adversarial perturbations, especially for large size images.
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