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Found 8 papers, 2 papers with code
SdCT-GAN: Reconstructing CT from Biplanar X-Rays with Self-driven Generative Adversarial Networks
Computed Tomography (CT) is a medical imaging modality that can generate more informative 3D images than 2D X-rays.
Dropout with Tabu Strategy for Regularizing Deep Neural Networks
Tabu Dropout has no extra parameters compared with the standard Dropout and also it is computationally cheap.
Advancing Tabu and Restart in Local Search for Maximum Weight Cliques
Our new restart strategy is based on the re-occurrence of a local search scenario instead of that of a candidate solution.
Trainable back-propagated functional transfer matrices
In experiments, it is demonstrated that the revised rules can be used to train a range of functional connections: 20 different functions are applied to neural networks with up to 10 hidden layers, and most of them gain high test accuracies on the MNIST database.
Learning of Human-like Algebraic Reasoning Using Deep Feedforward Neural Networks
Briefly, in a reasoning system, a deep feedforward neural network is used to guide rewriting processes after learning from algebraic reasoning examples produced by humans.
Normative Multiagent Systems: A Dynamic Generalization
Social norms are powerful formalism in coordinating autonomous agents' behaviour to achieve certain objectives.
NuMVC: An Efficient Local Search Algorithm for Minimum Vertex Cover
These two strategies are used in designing a new MVC local search algorithm, which is referred to as NuMVC.
Variable Forgetting in Reasoning about Knowledge
Given a background knowledge base and a set of observable variables for each agent, we show that the notion of an agent knowing a formula can be defined as a weakest sufficient condition of the formula under background knowledge base.
