Logic Tensor Network (LTN) is a Neural-Symbolic (NeSy) framework which supports learning of neural networks using the satisfaction of a first-order logic knowledge base as an objective. In other words ...

Yet this triumphant moment capped a journey spanning nearly 70 years, one marked by visionary early breakthroughs, a devastating critique that nearly killed the field, decades of quiet work in ...

This paper investigates the combined potential of neuromorphic and edge computing to develop a flexible machine learning (ML) system designed for processing data from dynamic vision sensors. We build ...

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The ecosystem will be guided by the principles of ethics, inclusion and sustainability. VANCOUVER — Quantum Algorithms Institute is creating a Centre for Responsible Quantum Innovation and Technology ...

Abstract: In this paper, we showed a method to forecast the stock price using neural networks. Predicting the stock market is very difficult since it depends on several known and unknown factors. In ...

Deep learning (DL) systems have been widely adopted in many industrial and business applications, dramatically improving human productivity, and enabling new industries. However, deep learning has a ...

Because of the popularity of smartphones and tablets, as well as the growth of television channels, computer games, and educational applications, children and teenagers are spending more amount of ...

However, implementing trained mathematical transformations by designing hardware for strict, operation-by-operation mathematical isomorphism is not the only way to perform efficient machine learning.

Global warming has put a significant strain on resources, and hence, economic opportunities, military considerations, and trade. The development of Arctic shipping routes is necessary to compensate ...