Researchers at Shanghai University have developed a physics-constrained, data-efficient artificial intelligence framework ...
Biclustering is a problem in machine learning and data mining that seeks to group together rows and columns of a dataset according to certain criteria. In this work, we highlight the natural relation ...
ABSTRACT: Discrete curves are composed of a set of ordered discrete points distributed at the intersection of the scanning plane and the surface of the object. In order to accurately calculate the ...
Researchers at Paderborn University in Germany have successfully set up Europe’s largest sampling-based photonic computer. Dubbed Paderborn Quantum Sampler (PaQS), the quantum computer has been built ...
Researchers from the University of Chicago have presented a classical algorithm that simulates Gaussian boson sampling (GBS) experiments, challenging the notion of quantum advantage. Study: A new ...
Large language models (LLMs) like transformers are typically pre-trained with a fixed context window size, such as 4K tokens. However, many applications require processing much longer contexts, up to ...
Quantum optics, which encodes information in the states of light, is privileged to havecomplexity-theoretic evidence supporting a scheme for quantum advantage that is native tothe platform – boson ...
A recent study published in Nature Physics proposed a quantum-inspired classical algorithm for solving zero-temperature cases in Gaussian boson sampling, revealing that these problems do not ...
Projecting a dynamic system’s future behaviour, or dynamics forecasting, entails understanding the underlying dynamics that drive the system’s evolution to make precise predictions about its future ...
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