Publications associées à A Linear-Quadratic Gaussian Approach to Dynamic Information Acquisition

Less Conservatism, Stronger Robustness: Iterative Robust Gain-Scheduled Path Following Control of Autonomous Bus With Unstructured and Changing Dynamics

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Global existence for perturbations of the 2D stochastic Navier-Stokes equations with space-time white noise

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We prove global in time well-posedness for perturbations of the 2D stochastic Navier-Stokes equations partial derivative( t)u + u center dot del u = Delta u - del p + sigma + xi, u(0, center dot ) = u(0),div (u) = 0, driven by additive space-time white noi ...

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Bayesian Optimization (BO) is typically used to optimize an unknown function f that is noisy and costly to evaluate, by exploiting an acquisition function that must be maximized at each optimization step. Even if provably asymptotically optimal BO algorith ...

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Reliable data-driven decision-making through optimal transport

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This paper introduces a novel method for data-driven robust control of nonlinear systems based on the Koopman operator, utilizing Integral Quadratic Constraints (IQCs). The Koopman operator theory facilitates the linear representation of nonlinear system d ...

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Exploiting the Signal-Leak Bias in Diffusion Models

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Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

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Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

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Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...

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Recently, there has been an arms race of pose forecasting methods aimed at solving the spatio-temporal task of predicting a sequence of future 3D poses of a person given a sequence of past observed ones. However, the lack of unified benchmarks and limited ...

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Spectral Estimators for High-Dimensional Matrix Inference

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A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

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An Ultralow-Power Triaxial MEMS Accelerometer With High-Voltage Biasing and Electrostatic Mismatch Compensation

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Ieee-Inst Electrical Electronics Engineers Inc2024

Neutron-Gamma Noise Measurements in a Zero-Power Reactor Using Organic Scintillators

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Linear-Quadratic-Gaussian (LQG) control is a fundamental control paradigm that is studied in various fields such as engineering, computer science, economics, and neuroscience. It involves controlling a system with linear dynamics and imperfect observations ...

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Multi-agent Learning with Privacy Guarantees

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A multi-agent system consists of a collection of decision-making or learning agents subjected to streaming observations from some real-world phenomenon. The goal of the system is to solve some global learning or optimization problem in a distributed or dec ...

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Robust tunable acoustic impedance control on electroacoustic resonators for aircraft noise reduction

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