Call for Papers
We look forward to welcoming you to Minneapolis to participate in this stimulating workshop. We accept submission of 2-page extended abstracts. Accepted contributions will be arranged in the format of oral or poster presentations. The workshop is a venue to share recent research results with no published proceedings. The workshop accepts submission of review papers if they are clearly identified as such.
A graph signal is a signal in which relationships between its components follows the structure encoded in a weighted graph. The purpose of graph signal processing is to exploit this underlying structure to analyze and process graph signals. The last few years have seen significant progress in the development of theory, tools, and applications of graph signal processing. The Graph Signal Processing Workshop is a forum intended to disseminate ideas to a broader audience and to exchange ideas and experiences on the future path of this vibrant field.
TOPICS OF INTEREST
Sampling and recovery of graph signals
Graph filter and filter bank design
Uncertainty principles and other fundamental limits
Graph signal transforms
Graph filter identification
Graph topology inference
Statistical graph signal processing
Signal processing on high-order graphs
Non-linear graph signal processing
Geometric deep learning (graph CNNs/RNNs)
Reinforcement learning on graphs
Representation learning on graphs
Applications to image and video processing
Applications to neuroscience and other medical fields
Applications to economics and social networks
Applications to infrastructure networks (communication, transportation, power)
IMPORTANT DATES:
Extended to April 10, 2019
April 12, 2019
May 1, 2019
June 1, 2019