Abstract: In this paper, we present Gaussian Process Gauss-Newton (GPGN), an algorithm for non-parametric, continuous-time, nonlinear, batch state estimation. This work adapts the methods of Gaussian ...
Dharmesh Tailor, Alvaro H.C. Correia, Eric Nalisnick and Christos Louizos. "Approximating Full Conformal Prediction for Neural Network Regression with Gauss-Newton Influence." [ICLR2025] Qualcomm AI ...
Partial differential equation based inverse problem such as image reconstruction in electrical impedance tomography (EIT) often lead to non-convex optimization problems. These problems are also ...
Abstract: Light detection and ranging (LiDAR) is negatively affected by target signal attenuation and fog clutter interference in foggy conditions, complicating the accurate target extraction from fog ...
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