all AI news
An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional Filters. (arXiv:2201.08465v1 [cs.CV])
Jan. 24, 2022, 2:10 a.m. | Paul Gavrikov, Janis Keuper
cs.LG updates on arXiv.org arxiv.org
We present first empirical results from our ongoing investigation of
distribution shifts in image data used for various computer vision tasks.
Instead of analyzing the original training and test data, we propose to study
shifts in the learned weights of trained models. In this work, we focus on the
properties of the distributions of dominantly used 3x3 convolution filter
kernels. We collected and publicly provide a data set with over half a billion
filters from hundreds of trained CNNs, using …
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Senior ML Researcher - 3D Geometry Processing | 3D Shape Generation | 3D Mesh Data
@ Promaton | Europe
Data Architect
@ Western Digital | San Jose, CA, United States
Senior Data Scientist GenAI (m/w/d)
@ Deutsche Telekom | Bonn, Deutschland
Senior Data Engineer, Telco (Remote)
@ Lightci | Toronto, Ontario
Consultant Data Architect/Engineer H/F - Innovative Tech
@ Devoteam | Lyon, France
(Senior) ML Engineer / Software Engineer Machine Learning & AI (m/f/x) onsite or remote (in Germany or Austria)
@ Scalable GmbH | Wien, Germany