7th Graph Signal Processing Workshop (GSP 2024)

Following a series of successful workshops since 2016, we are pleased to announce that the 7th Edition of the Graph Signal Processing Workshop will be held June 24-26, 2024 in Delft, The Netherlands (campus TU Delft).

The workshop will provide a warm welcome to experts and practitioners from academia and industry in the field of graph signal processing (GSP). The goal of GSP is to generalize classical signal processing and statistical learning tools to signals on graphs (functions defined on a graph).

Important Dates

February 1, 2024	Submission open
March 15, 2024	Submission deadline
April 1, 2024	Notification of acceptance
April 14, 2024	Early registration
June 24-26, 2024	Workshop

Submission

We accept submissions of 2-page extended abstracts with standard IEEE or ACM format. 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. Authors are encouraged to send previously published papers as extended abstracts. Authors of accepted abstracts who are interested in further advertising their work are welcome to submit their abstract (or the full version of their work) to arXiv with the quote “This work was accepted to be presented at the Graph Signal Processing Workshop 2024”.

Submission and more information: gspworkshop.org/

If you have any questions regarding submission or inquiries about the workshop, please contact gspworkshop2024@gmail.com.

Areas of interest

The last few years have seen significant progress in the development of theory, tools, and applications of graph signal processing, as well as of related fields such as graph machine learning. 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 include but are not limited to:

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 higher-order networks;
Non-linear graph signal processing;
Signal processing on dynamic graphs;
Joint time-vertex signal processing;
Prediction and learning in graphs;
Graph-based machine learning;
Geometric deep learning (graph NNs/CNNs/RNNs);
Representation learning on graphs;
Reinforcement 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 (e.g., communication, transportation, power networks).

Organising Committee

Geert Leus, General Chair
Elvin Isufi, General Co-Chair
Antonio Marques, Technical Program Chair
Samuel Rey, Technical Program Co-Chair
Gonzalo Mateos, Invited Speakers Chair
Santiago Segarra, Industry Liaison Chair
Luana Ruiz, Publicity Chair