One of the key challenges of building effective AI agents is teaching them to choose between using external tools or relying on their internal knowledge. But large language models are often trained to ...
Most enterprise RAG pipelines are optimized for one search behavior. They fail silently on the others. A model trained to synthesize cross-document reports handles constraint-driven entity search ...
This Unity asset provides an end-to-end, Human-in-the-Loop (HITL) Bayesian Optimization workflow (single- and multi-objective) built on botorch.org. It lets you declare design parameters and ...
ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...
Data-driven models that act as surrogates for computationally costly 3D topology optimization techniques are very popular because they help alleviate multiple time-consuming 3D finite element analyses ...
Introduction: Synthetic vascular grafts have been widely used in clinical practice for aortic replacement surgery. Despite their high rates of surgical success, they remain significantly less ...
Abstract: Python has become the programming language of choice for research and industry projects related to data science, machine learning, and deep learning. Since optimization is an inherent part ...
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