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ATEM is a novel framework for studying topic evolution in scientific archives. ATEM is based on dynamic topic modeling and dynamic graph embedding techniques that explore the dynamics of content and citations of documents within a scientific corpus. ATEM explores a new notion of contextual emergence for the discovery of emerging interdisciplinary research topics based on the dynamics of citation links in topic clusters. Our experiments show that ATEM can efficiently detect emerging cross-disciplinary topics within the DBLP archive of over five million computer science articles. paper: https://arxiv.org/abs/2306.02221

This is a tool intended to monitor the GPU usage on the various GPU-servers at the LIP6 Lab, Paris

Supplementary material for the paper "Deep Neural Networks Under Stress", ICIP 2016

Encode unicode strings in a silly way, based on glounicode

Cross domain dynamic

A cross-platform Docker solution to mitigate WebRTC IP address leaks in Linux, macOS, and Windows. GPL-3.0-or-later.

GitLab repository mirror of the main repository: https://github.com/snowpackvipn/preventing-webrtc-ip-address-leaks. SoftwareHeritage: swh:1:dir:13dd58fbbff37434ad0432da7ca69c84ea4eb9a4.

Static Timing Analyser

A blockgraph for mesh networks

NLP course at ESILV, 10/01/2019

Uniform precision variant