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Found 4 papers, 3 papers with code
A Neural-Symbolic Framework for Mental Simulation
We present a neural-symbolic framework for observing the environment and continuously learning visual semantics and intuitive physics to reproduce them in an interactive simulation.
Hacking Neural Networks: A Short Introduction
A large chunk of research on the security issues of neural networks is focused on adversarial attacks.
Adding Intuitive Physics to Neural-Symbolic Capsules Using Interaction Networks
Many current methods to learn intuitive physics are based on interaction networks and similar approaches.
A Neural-Symbolic Architecture for Inverse Graphics Improved by Lifelong Meta-Learning
We follow the idea of formulating vision as inverse graphics and propose a new type of element for this task, a neural-symbolic capsule.
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