main webpage W Topic Physics arXiv (Cornell University) Learning Deep Dynamical Systems using Stable Neural ODEs 2024 Learning complex trajectories from demonstrations in robotic tasks has been effectively addressed through the utilization of Dynamical Systems (DS). State-of-the-art DS learning methods ensure stability of the generated trajectories; however, they have three … Article Open Physics Open Article Page

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Science about matter and energy Physics is the natural science that studies matter, its fundamental constituents, its motion and behavior through space and time, and the related entities of energy and force. Physics is one of the most fundamental scientific disciplines, with its main goal being to understand how the universe behaves. A scientist who specializes in the field of physics is called a physicist. Physics is one of the oldest academic disciplines and, through its inclusion of astronomy, perhaps the oldest. Over much of the past two millennia, physics, chemistry, biology, and certain branches of mathematics were a part of natural philosophy, but during the Scientific Revolution in the 17th century these natural sciences emerged as unique research endeavors in their own right. Critical Symbolic Virtual Narrative Open Physics Open Article Page

Exploring foci of: arXiv (Cornell University) Learning Deep Dynamical Systems using Stable Neural ODEs 2024 Learning complex trajectories from demonstrations in robotic tasks has been effectively addressed through the utilization of Dynamical Systems (DS). State-of-the-art DS learning methods ensure stability of the generated trajectories; however, they have three shortcomings: a) the DS is assumed to have a single attractor, which limits the diversity of tasks it can achieve, b) state derivative information is assumed to be available in the learning process and c) the state of the DS is assumed to be measurable at infe… Open Article Page

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Explore Physics W Topic Physics arXiv (Cornell University) Learning Deep Dynamical Systems using Stable Neural ODEs 2024 Learning complex trajectories from demonstrations in robotic tasks has been effectively addressed through the utilization of Dynamical Systems (DS). State-of-the-art DS learning methods ensure stability of the generated trajectories; however, they have three … Article Critical Symbolic Virtual Narrative Open Physics Open Article Page