Multi-objective optimisation using evolutionary algorithms constitutes a powerful computational framework that addresses complex problems involving conflicting objectives. By emulating natural ...
The intersection of evolutionary algorithms and data-driven optimisation is reshaping materials science by offering novel computational frameworks for designing and refining materials. Drawing ...
Large language models (LLMs) leverage unsupervised learning to capture statistical patterns within vast amounts of text data. At the core of these models lies the Transformer architecture, which ...
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