About 0 results
AI Overview
Generating...
Sponsored
• AdSense Integration Active
arxiv.org arXiv
arxiv.org › abs › 2301.00942v1
These notes were compiled as lecture notes for a course developed and taught at the University of the Southern California. They should be accessible to a typical engineering graduate student with a st...
arxiv.org arXiv
arxiv.org › abs › 2012.06469v1
We consider the generic deep image enhancement problem where an input image is transformed into a perceptually better-looking image. Recent methods for image enhancement consider the problem by perfor...
arxiv.org arXiv
arxiv.org › abs › 1912.06732v2
Deep neural networks and the ENO procedure are both efficient frameworks for approximating rough functions. We prove that at any order, the ENO interpolation procedure can be cast as a deep ReLU neura...
arxiv.org arXiv
arxiv.org › abs › 2107.09957v2
Deep Neural Networks, often owing to the overparameterization, are shown to be capable of exactly memorizing even randomly labelled data. Empirical studies have also shown that none of the standard re...
arxiv.org arXiv
arxiv.org › abs › 2306.11113v2
Evidential deep learning, built upon belief theory and subjective logic, offers a principled and computationally efficient way to turn a deterministic neural network uncertainty-aware. The resultant e...
arxiv.org arXiv
arxiv.org › abs › 1811.00913v1
In 1989, Dicks and Dunwoody proved the Almost Stability Theorem, which has among its corollaries the Stallings-Swan theorem that groups of cohomological dimension one are free. In this article, we use...
arxiv.org arXiv
arxiv.org › abs › 1903.03040v2
Many large scale problems in computational fluid dynamics such as uncertainty quantification, Bayesian inversion, data assimilation and PDE constrained optimization are considered very challenging com...
arxiv.org arXiv
arxiv.org › abs › 2107.02926v2
Inverse problems are ubiquitous in nature, arising in almost all areas of science and engineering ranging from geophysics and climate science to astrophysics and biomechanics. One of the central chall...
arxiv.org arXiv
arxiv.org › abs › 2011.03712v1
Recently, there is a vast interest in developing image feature learning methods that are independent of the training data, such as deep image prior, InGAN, SinGAN, and DCIL. These methods are unsuperv...
arxiv.org arXiv
arxiv.org › abs › 0810.2734v1
Recently Dicks-Linnell determined the $L^2$-Betti numbers of the orientable surface-plus-one-relation groups, and their arguments involved some results that were obtained topologically by Hempel and H...