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https://openreview.net/forum?id=pZCYG7gjkKz Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr\"om Method | OpenReview Transformers are expensive to train due to the quadratic time and space complexity in the self-attention mechanism. On the other hand, although kernel machines... self attention gaussian kernel https://openreview.net/forum?id=ZgIJs67nw3&referrer=%5Bthe%20profile%20of%20Ruotao%20Xu%5D(%2Fprofile%3Fid%3D~Ruotao_Xu1) Deep Single Image Defocus Deblurring via Gaussian Kernel Mixture Learning | OpenReview This paper proposes an end-to-end deep learning approach for removing defocus blur from a single defocused image. Defocus blur is a common issue in digital... single image gaussian kernel deep defocus deblurring https://openreview.net/forum?id=kSR-_SVzDR- Gaussian Kernel Mixture Network for Single Image Defocus Deblurring | OpenReview A lightweight DNN for single image defocus deblurring with SOTA performance gaussian kernel single image mixture network defocus https://www.iit.edu/events/function-approximation-using-gaussian-kernel Function Approximation Using Gaussian Kernel | Illinois Institute of Technology function approximation gaussian kernel using illinois institute https://arxiv.org/abs/2409.03891 [2409.03891] Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or... Abstract page for arXiv paper 2409.03891: Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality gaussian kernel https://openreview.net/forum?id=S0xrBMFihS Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel | OpenReview The problem of efficient approximation of a linear operator induced by the Gaussian or softmax kernel is often addressed using random features (RFs) which... https://deepai.org/publication/heat-kernel-and-intrinsic-gaussian-processes-on-manifolds Heat kernel and intrinsic Gaussian processes on manifolds | DeepAI Jun 25, 2020 - 06/25/20 - There is an increasing interest in the problem of nonparametric regression like Gaussian processes with predictors locating on man... heat kernel gaussian processes intrinsic manifolds deepai https://openreview.net/forum?id=yKvHJJE9le Safe Time-Varying Optimization based on Gaussian Processes with Spatio-Temporal Kernel | OpenReview Ensuring safety is a key aspect in sequential decision making problems, such as robotics or process control. The complexity of the underlying systems often... https://www.kth.se/math/kalender/christian-rose-gaussian-upper-heat-kernel-bounds-and-faber-krahn-inequalities-on-graphs-with-unbounded-geometry-1.1355116?date=2024-09-11&orgdate=2024-02-13&length=1&orglength=0 Christian Rose: Gaussian upper heat kernel bounds and Faber-Krahn inequalities on graphs with... https://openreview.net/forum?id=zUiH8UUYDo Scalable Deep Kernel Gaussian Process for Vehicle Dynamics in Autonomous Racing | OpenReview In this work, we have proven that DKL-SKIP, as a scalable deep kernel learning for Gaussian Process, is a promising tool for modeling complex vehicle dynamics... gaussian process https://openreview.net/forum?id=o1woLLxcpv Implications of Gaussian process kernel mismatch for out-of-distribution data | OpenReview Gaussian processes provide reliable uncertainty estimates in nonlinear modeling, but a poor choice of the kernel can lead to poor generalization. Although... gaussian process implications kernel