Persistent Weak Interferer Detection in WiFi Networks: A Deep Learning Based Approach

no code implementations • 23 May 2022 • Andrew Adams, Richard F. Obrecht, Miller Wilt, Daniel Barcklow, Bennett Blitz, Daniel Chew

In this paper, we explore the use of multiple deep learning techniques to detect weak interference in WiFi networks.

Metric Learning

Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions

4 code implementations • 13 Feb 2018 • Nicolas Vasilache, Oleksandr Zinenko, Theodoros Theodoridis, Priya Goyal, Zachary DeVito, William S. Moses, Sven Verdoolaege, Andrew Adams, Albert Cohen

Deep learning models with convolutional and recurrent networks are now ubiquitous and analyze massive amounts of audio, image, video, text and graph data, with applications in automatic translation, speech-to-text, scene understanding, ranking user preferences, ad placement, etc.

BIG-bench Machine Learning Management +2

Fast Bilateral-Space Stereo for Synthetic Defocus

no code implementations • CVPR 2015 • Jonathan T. Barron, Andrew Adams, YiChang Shih, Carlos Hernandez

Given a stereo pair it is possible to recover a depth map and use that depth to render a synthetically defocused image.

Fast High-Dimensional Filtering Using the Permutohedral Lattice

no code implementations • Eurographics 2010 • Andrew Adams, Jongmin Baek, Myers Abraham Davis

Many useful algorithms for processing images and geometry fall under the general framework of high-dimensional Gaussian filtering.

Vocal Bursts Intensity Prediction