SPTM-L4.5

END-TO-END LEARNING OF GAUSSIAN MIXTURE PROPOSALS USING DIFFERENTIABLE PARTICLE FILTERS AND NEURAL NETWORKS

Benjamin Cox, University of Edinburgh, United Kingdom of Great Britain and Northern Ireland; Sara Perez-Vieites, IMT Nord Europe, France; Nicolas Zilberstein, Martin Sevilla, Santiago Segarra, Rice University, United States of America; Víctor Elvira, University of Edinburgh, United Kingdom of Great Britain and Northern Ireland

Session:
SPTM-L4: Bayesian Signal Processing Lecture

Track:
Signal Processing Theory and Methods

Location:
Room 201

Presentation Time:
Wed, 17 Apr, 17:50 - 18:10 (UTC +9)

Session Co-Chairs:
Petar Djuric, Stony Brook University and Nir Shlezinger, Ben-Gurion University
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