This essay is based in part on presentations given in the Spring and Summer of 2018 at the Creative AI Meetup at the Photographer’s Gallery in London, the University of Chicago’s Franke Institute for the Humanities, the Aarhus Institute of Advanced Studies in Denmark, INRS in Quebec, and the University of Warwick Centre for Interdisciplinary Methodologies Research Forum. It is the second part of a longer discussion about deep learning, the first part of which is in the essay, “Deep Learning as an Epistemic Ensemble”.
Implementation and demo of explainable coding of clinical notes with Hierarchical Label-wise Attention Networks (HLAN) - acadTags/Explainable-Automated-Medical-Coding
Menschen können sich bis zu 8000 verschiedene Gesichter merken und unterscheiden, weit mehr als jede KI-Software. Das überrascht, wenn man sich die Erfolgsmeldungen zur Künstlichen Intelligenz vor Augen führt. Was steckt also hinter dem Hype, und was ist Realität?
Dive into deep reinforcement learning by training a model to play the classic 1970s video game Pong — using Keras, FloydHub, and OpenAI's "Spinning Up."
meta description: Making a deep convolutional neural network smaller and faster.
A user-friendly explanation how to compress CNN models - by removing full filters filters from a layer (GPU friendly, unlike sparse layers). L1-norm used for picking candidates for removal. Optimized MobileNet by 25%.
Kubernetes-GPU-Guide - This guide should help fellow researchers and hobbyists to easily automate and accelerate there deep leaning training with their own Kubernetes GPU cluster.
The limitations of backpropagation learning can now be overcome by using multilayer neural networks that contain top-down connections and training them to /generate/ sensory data rather than to classify it. (...) much better than previous approaches
M. Springstein, S. Schneider, C. Althaus, und R. Ewerth. MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10 - 14, 2022, Seite 1107--1116. ACM, (2022)
F. Hoppe, D. Dessì, und H. Sack. Companion Proceedings of the Web Conference 2021, Seite 417--421. Association for Computing Machinery, (2021)event-place: Virtual Conference.
F. Hoppe, D. Dess\`ı, und H. Sack. Companion of The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021, Seite 417--421. ACM / IW3C2, (2021)