by instadatahelp | Sep 3, 2023 | AI Blogs
Universal Metric Embeddings with Small Transformers Anastasis Kratsios, Valentin Debarnot, Ivan Dokmanić; 24(170):1−48, 2023. Abstract This study focuses on representing data from an arbitrary metric space $\mathcal{X}$ in the space of univariate Gaussian mixtures...
by instadatahelp | Sep 3, 2023 | AI Blogs
[Submitted on 31 Aug 2023] Download a PDF of the paper titled “What can we learn from quantum convolutional neural networks?” by Chukwudubem Umeano and 3 other authors Download PDF Abstract: This paper analyzes quantum convolutional neural networks (QCNNs)...
by instadatahelp | Sep 3, 2023 | AI Blogs
Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous Bias-Variance Reduction and Supercanonical Convergence Authors: Henry Lam, Haofeng Zhang; Journal of Machine Learning Research, 24(85):1−58, 2023. Abstract The standard Monte Carlo computation is...
by instadatahelp | Sep 3, 2023 | AI Blogs
arXivLabs is a platform where collaborators can develop and share new features for arXiv directly on our website. Both individuals and organizations that collaborate with arXivLabs share our values of openness, community, excellence, and user data privacy. We are...
by instadatahelp | Sep 3, 2023 | AI Blogs
Incremental Learning in Diagonal Linear Networks Raphaël Berthier; 24(171):1−26, 2023. Abstract This paper discusses the trajectory of the gradient flow in Diagonal Linear Networks (DLNs) when initialized with small values. DLNs are simplified artificial neural...
by instadatahelp | Sep 3, 2023 | AI Blogs
[Submitted on 31 Aug 2023] Download a PDF of the paper titled Generate Your Own Scotland: Satellite Image Generation Conditioned on Maps, by Miguel Espinosa and 1 other authors Download PDF Abstract: Despite recent advancements in image generation, diffusion models...
