Abstract: Optimal control of unknown nonlinear systems is challenging due to the absence of the underlying dynamics model. Reinforcement learning (RL) has become an effective framework for such ...
Complex network theory has become a key analytical framework in modern physics for studying structure, dynamics, and emergent behaviour in complex systems.
MapAnything is an open-source research framework for universal metric 3D reconstruction. At its core is a simple, end-to-end trained transformer model that directly regresses the factored metric 3D ...
Machine learning-driven carrier risk modeling enables supply chains to predict and prevent pickup defects, reducing costs and improving on-time performance.
Three LangChain flaws enable data theft across LLM apps, affecting millions of deployments, exposing secrets and files.
Abstract: Nonlinear model predictive control (NMPC) algorithms have been widely used in autonomous vehicle trajectory tracking, yet their performance is primarily limited by the accuracy of the ...
"description": "PyData Chicago 2016\n\nGenotype-phenotype studies are done for predicting traits such as whether someone will go bald or have a particular disease given their only genome. We look at ...
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