MLSP-L21.1
SEQUENTIAL MONTE CARLO GRAPH CONVOLUTIONAL NETWORK FOR DYNAMIC BRAIN CONNECTIVITY
Fengfan Zhao, Ercan Engin Kuruoglu, Tsinghua University, China
Session:
MLSP-L21: Learning Theory and Methods Lecture
Track:
Machine Learning for Signal Processing
Location:
Room E3
Presentation Time:
Fri, 19 Apr, 08:20 - 08:40 (UTC +9)
Session Co-Chairs:
Ercan E Kuruoglu, Tsinghua Shenzhen International Graduate School and Abhisek Chakraborty, Texas A&M University
Session MLSP-L21
MLSP-L21.1: SEQUENTIAL MONTE CARLO GRAPH CONVOLUTIONAL NETWORK FOR DYNAMIC BRAIN CONNECTIVITY
Fengfan Zhao, Ercan Engin Kuruoglu, Tsinghua University, China
MLSP-L21.2: PROBABILISTIC SPIKE TRAIN INFERENCE
Abhisek Chakraborty, Texas A&M University, United States of America
MLSP-L21.3: LEARNED LAYERED CODING FOR SUCCESSIVE REFINEMENT IN THE WYNER-ZIV PROBLEM
Boris Joukovsky, Brent De Weerdt, Nikos Deligiannis, Vrije Universiteit Brussel, Belgium
MLSP-L21.4: UNDERSTANDING PROBE BEHAVIORS THROUGH VARIATIONAL BOUNDS OF MUTUAL INFORMATION
Kwanghee Choi, Jee-weon Jung, Shinji Watanabe, Carnegie Mellon University, United States of America
MLSP-L21.5: MINIMIZING LOW-RANK MODELS OF HIGH-ORDER TENSORS: HARDNESS, SPAN, TIGHT RELAXATION, AND APPLICATIONS
Nicholas Sidiropoulos, Paris Karakasis, University of Virginia, United States of America; Aritra Konar, KU Leuven, Belgium
MLSP-L21.6: Principled Pruning of Bayesian Neural Networks through Variational Free Energy Minimization
Jim Beckers, Bart van Erp, Ziyue Zhao, Kirill Kondrashov, Bert de Vries, Eindhoven University of Technology Ringgold standard institution - Electrical Engineering Eindhoven Netherlands
and
GN Hearing AS Ringgold standard institution Eindhoven Netherlands
Contacts