Tag: system
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Machine learning assisted state prediction of misspecified linear dynamical system via modal reduction
Machine learning assisted state prediction of misspecified linear dynamical system via modal reduction arXiv:2601.05297v1 Announce Type: new Abstract: Accurate prediction of structural dynamics is imperative for preserving digital twin fidelity throughout operational lifetimes. Parametric models with fixed nominal parameters often omit critical physical effects due to simplifications in geometry, material behavior, damping, or boundary conditions,…
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Building a Monitoring System That Actually Works
Building a Monitoring System That Actually Works A step-by-step guide to catching real anomalies without drowning in false alerts The post Building a Monitoring System That Actually Works appeared first on Towards Data Science. Mariya Mansurova Go to original source
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Stop Feeling Lost : How to Master ML System Design
Stop Feeling Lost : How to Master ML System Design What machine learning system design is and how to prepare for it The post Stop Feeling Lost : How to Master ML System Design appeared first on Towards Data Science. Egor Howell Go to original source
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Building a Video Game Recommender System with FastAPI, PostgreSQL, and Render: Part 2
Building a Video Game Recommender System with FastAPI, PostgreSQL, and Render: Part 2 Deploying a FastAPI + PostgreSQL recommender system as a web application on Render The post Building a Video Game Recommender System with FastAPI, PostgreSQL, and Render: Part 2 appeared first on Towards Data Science. Lucas See Go to original source
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Bayesian Inference and Learning in Nonlinear Dynamical Systems: A Framework for Incorporating Explicit and Implicit Prior Knowledge
Bayesian Inference and Learning in Nonlinear Dynamical Systems: A Framework for Incorporating Explicit and Implicit Prior Knowledge arXiv:2508.15345v1 Announce Type: new Abstract: Accuracy and generalization capabilities are key objectives when learning dynamical system models. To obtain such models from limited data, current works exploit prior knowledge and assumptions about the system. However, the fusion of…
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Attractors in Neural Network Circuits: Beauty and Chaos
Attractors in Neural Network Circuits: Beauty and Chaos The state space of the first two neuron activations over time follows an attractor. What is one thing in common between memories, oscillating chemical reactions and double pendulums? All these systems have a basin of attraction for possible states, like a magnet that draws the system towards certain…
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dynoGP: Deep Gaussian Processes for dynamic system identification
dynoGP: Deep Gaussian Processes for dynamic system identification arXiv:2502.05620v1 Announce Type: new Abstract: In this work, we present a novel approach to system identification for dynamical systems, based on a specific class of Deep Gaussian Processes (Deep GPs). These models are constructed by interconnecting linear dynamic GPs (equivalent to stochastic linear time-invariant dynamical systems) and…