Following a series of successful workshops since 2016, we are pleased to announce that the 6th Edition of the Graph Signal Processing Workshop will be held June 12-14 in Oxford, UK as an in-person event.
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). The workshop will invite discussion on theoretical and foundational topics related to GSP, including graph transforms, sampling theorems, and filter design. The workshop will also highlight how such tools can be integrated into a learning framework, and show novel theoretical developments at the intersection of graph signal processing and graph machine learning. Examples of applications that will be showcased in the workshop include gene expression patterns defined on top of gene networks, the spread of epidemics over a social network, the congestion level at the nodes of a telecommunication network, and patterns of brain activity defined on top of a brain network.
- [2023/02/01] Submission is now open. Guilelines can be found on the “Call for papers” page.
- Submission open: February 1, 2023
- Submission deadline: March 1, 2023
- Notification of acceptance: March 15, 2023
- Early registration: April 1, 2023
- Workshop: June 12-14, 2023
- Xiaowen Dong (University of Oxford)
- Antonio Marques (King Juan Carlos University)
- Gonzalo Mateos (University of Rochester)
- Santiago Segarra (Rice University)
- Dorina Thanou (École Polytechnique Fédérale de Lausanne)
- Laura Toni (University College London)
Local Organizing Team
- Keyue Jiang (University College London)
- Henry Kenlay (University of Oxford)
If you have any questions regarding submission or enquiries about the workshop, please get in touch via email: firstname.lastname@example.org