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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

Mining Algorithm Patterns

Implementation of Prog&Play on Spring Engine v0.82.5.1 and v100.0

Alliance/Coriolis Toolkit & Checker contain various design flow examples, blocks or full chips. It is also used as a regression test for all the tools.

The bulk of the code developed during my PhD thesis « Efficient multiword matrix product algorithm using floating-point arithmetic over finite prime fields » (not yet defended/nor published).