Access a .pdf version of the technical program and the program-at-a-glance here.

Program-At-A-Glance

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General Information

Lectures in the oral sessions are 20-minutes long (including Q&As). The format of posters is flexible, but A0 size and portrait orientation are recommended.

There will be a single poster session per day. The session takes place during two different time slots (13h00 to 14h00 and 15h00 to 16h00) but the posters will be the same.

Plenary Talks

Plenary Mon-AM (Monday 9:00 - 10:00)

Georgios B. Giannakis, University of Minnesota

Plenary Mon-PM (Monday 14:00 - 15:00)

Francesca Parise, Cornell University

Plenary Tue-AM (Tuesday 9:00 - 10:00)

Sergio Barbarossa, Sapienza University of Rome

Plenary Tue-PM (Tuesday 14:00 - 15:00)

Stefan Vlaski, Imperial College London

Plenary Wed-AM (Wednesday 9:00 - 10:00)

Piet Van Mieghem, TU Delft

Plenary Wed-PM (Wednesday 14:00 - 15:00)

Smita Krishnaswamy, Yale University

Oral Sessions

Oral Session Mon-AM (Monday 10:30 - 12:30) - Network Topology Inference
  • Paper 1: A Novel Smoothness Prior for Hypergraph Machine Learning, Bohan Tang (ID: 58)
  • Paper 2: Mitigating subpopulation bias for fair network topology inference, Madeline Navarro (ID: 33)
  • Paper 3: Inferring the Topology of a Networked Dynamical Systems, Augusto Santos (ID: 88)
  • Paper 4: Sampling and Consensus for Anomalous Edge Detection, Panagiotis Traganitis (ID: 80)
  • Paper 5: Introducing Graph Learning over Polytopic Uncertain Graph, Masako Kishida (ID: 5)
  • Paper 6: Laplacian-Constrained Cram r-Rao Bound for Networks Applications, Morad Halihal (ID: 73)
Oral Session Mon-PM (Monday 16:00 - 17:40): Graph filters
  • Paper 1: Median Autoregressive Graph Filters, David Tay (ID: 12)
  • Paper 2: On the Stability of Graph Spectral Filters: A Probabilistic Perspective, Ning Zhang, (ID: 79)
  • Paper 3: Algebraic spaces of filters for signals on graphons, Juan Andr s Bazerque (ID: 60)
  • Paper 4: Graph Filtering for Clustering Attributed Graphs, Meiby Ortiz-Bouza (ID: 40)
  • Paper 5: HoloNets: Spectral Convolutions do extend to Directed Graphs, Christian Koke (ID: 4)
Oral Session Tue-AM (Tuesday 10:30 - 12:30) - Signal processing on higher-order networks
  • Paper 1: Disentangling the Spectral Properties of the Hodge Laplacian: Not All Small Eigenvalues Are Equal, Vicent P. Grande (ID: 32)
  • Paper 2: Simplicial Vector Autoregressive Models, Rohan Money (ID: 28).
  • Paper 3: Learning Graphs and Simplicial Complexes from Data, Andrei Buciulea (ID: 22)
  • Paper 4: Topological Dictionary Learning, Paolo Di Lorenzo (ID: 24)
  • Paper 5: Hyperedge Representations with Deep Hypergraph Wavelets: Applications to Spatial Transcriptomics, Xingzhi Sun, (ID: 81)
  • Paper 6: Presentation by Mathworks
Oral Session Tue-PM (Tuesday 16:00 - 17:20) - Graph learning
  • Paper 1: Graph Topology Learning with Functional Priors, Hoi-To Wai (ID: 45)
  • Paper 2: Enhanced Graph-Learning Schemes Driven by Similar Distributions of Motifs, Samuel Rey (ID: 55)
  • Paper 3: Heterogeneous Graph Structure Learning: A Statistical Perspective, Keyue Jiang (ID: 38)
  • Paper 4: Graph Structure Learning with Interpretable Bayesian Neural Networks, Max Wasserman (ID: 21)
Oral Session Wed-AM (Wednesday 10:30 - 12:30) - Geometric deep learning
  • Paper 1: Online Time Covariance Neural Networks, Andrea Caballo (ID: 50)
  • Paper 2: From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module, Claudio Battiloro (ID: 23)
  • Paper 3: Graph Convolutional Neural Networks in the Companion Model, Shreyas Chaudhari (ID: 67)
  • Paper 4: Representing Edge Flows on Graphs via Sparse Cell Complexes, Josef Hoppe (ID: 3)
  • Paper 5: Multi-Scale Hydraulic Graph Neural Networks, Roberto Bentivoglio, (ID: 59)
  • Paper 6: Simplicial Scattering Networks, Sundeep Chepuri (ID: 48)
Oral Session Wed-PM (Wednesday 16:00 - 17:40) - GSP Theory and Methods
  • Paper 1: Discrete Integral Operators for Graph Signal Processing, Naoki Saito (ID: 8)
  • Paper 2: M bius Total Variation for Directed Acyclic Graph, Vedran Mihal (ID: 34)
  • Paper 3: Involution-Based Graph-Signal Processing, Gerald Matz (ID: 49)
  • Paper 4: Blind Deconvolution of Sparse Graph Signals in the Presence of Perturbations, Victor M. Tenorio (ID: 77)
  • Paper 5: Quantile-based fitting for graph signals, Kyusoon Kim (ID: 64)

Poster Sessions

Poster Session Mon (Monday 13:00-14h00 & 15h00-16h00) - Euler
  • Paper 1: Decentralized and Lifelong-Adaptive Multi-Agent Collaborative Learning, Shuo Tang (ID: 61)
  • Paper 2: Online Graph Learning Via Proximal Newton Method from Streaming Data, Carrson Fung (ID: 70)
  • Paper 3: Online Graph Filtering Over Expanding Graphs, Bishwadeep Das (ID: 53)
  • Paper 4: Hodge-Aware Matched Subspace Detectors, Chengen Liu (D: 15)
  • Paper 5: Windowed Hypergraph Fourier Transform and Vertex-frequency Representation, Alcebiades Dal Col (ID: 35)
  • Paper 6: Graph Signal Processing: The 2D Companion Model, John Shi (ID: 66)
  • Paper 7: Robust Graph Learning for Classification, Jingxin Zhang (ID: 47)
  • Paper 8: Sparse Recovery of Diffused Graph Signals, Gal Morgenstern (ID: 14)
  • Paper 9: Learning Stochastic Graph Neural Networks with Constrained Variance, Elvin Isufi (ID: 27)
  • Paper 10: On the Impact of Sample Size in Reconstructing Signals with Graph Laplacian Regularisation, Baskaran Sripathmanathan (ID: 86)
  • Paper 11: Hypergraph Transformer for Semi-Supervised Classification, Bohan Tang (ID: 68)
  • Paper 12: Convolutional GNN to process signals defined over DAGs, Samuel Rey (ID: 87)
  • Paper 13: Graph Neural Networks with Adaptive Structure, Ziping Zhao (ID: 26)
  • Paper 14: Efficient Task Planning with Taxonomy Graph States and Large Language Models, Zhaoting Li (ID: 51)
  • Paper 15: Sampling sparse graph signals, Stefan Kunis (ID: 7)
  • Paper 16: Learned Finite-Time Consensus for Distributed Optimization, Aaron Fainman (ID: 78)
  • Paper 17: Framelet Message Passing, Yuguang Wang (ID: 29)
Poster Session Tue (Tuesday 13:00-14h00 & 15h00-16h00) - Laplace
  • Paper 1: ResolvNet: A Graph Convolutional Network with multi-scale Consistency, Christian Koke, (ID: 37)
  • Paper 2: Multiscale Graph Signal Clustering, Reina Kaneko (ID: 18)
  • Paper 3: On Stability of GCNN Under Graph Perturbations, Jun Zhang (ID: 72)
  • Paper 4: Kernel graph filtering – a new method for dynamic sinogram denoising, Jingxin Zhang (ID: 42)
  • Paper 5: Data-Aware Dynamic Network Decomposition, Bishwadeep Das (ID: 56)
  • Paper 6: Hodge-Compositional Edge Gaussian Processes, Maosheng Yang (ID: 13)
  • Paper 7: Estimators for Connection-Laplacian-Based Linear Algebra, Hugo Jaquard (ID: 36)
  • Paper 8: Recovering Missing Node Features with Local Structure-based Embeddings, Victor M. Tenorio (ID: 19)
  • Paper 9: Seeking universal approximation for continuous counterparts of GNNs on large random graphs, Matthieu Cordonnier (ID: 44)
  • Paper 10: Benchmarking Graph Neural Networks with the Quadratic Assignment Problem, Adrien Lagesse (ID: 54)
  • Paper 11: Inferring Time-Varying Signal over Uncertain Graphs, Mohammad Sabbaqi (ID: 84)
  • Paper 12: Optimal Quasi-clique: Hardness, Equivalence with Densest-k-Subgraph, and Quasi-partitioned Community Mining, Aritra Konar (ID: 9)
  • Paper 13: Learning Causal Influences from Social Interactions, Mert Kayaalp (ID: 11)
  • Paper 14: Peer-to-Peer Learning + Consensus with Non-IID Data, Srinivasa Pranav (ID: 69)
  • Paper 15: Community mining by modeling multilayer networks with Cartesian product graphs, Tiziana Cattai (ID: 65)
  • Paper 16: A Rewiring Contrastive Patch PerformerMixer Framework for Graph Representation Learning, Zhongtian Sun (ID: 75)
Poster Session 3 (Wednesday 13:00-14h00 & 15h00-16h00) - Erdos
  • Paper 1: Utilizing graph Fourier transform for automatic Alzheimer s disease detection from EEG signals, Ramnivas Sharma (ID: 6)
  • Paper 2: Emergence of Higher-Order Functional Brain Connectivity with Hypergraph Signal Processing, Breno C Bispo (ID: 10)
  • Paper 3: Protection Against Graph-Based False Data Injection Attacks on Power Systems, Gal Morgenstern (ID: 16)
  • Paper 4: Arbitrarily Sampled Signal Reconstruction Using Relative Difference Features, Chin-Yun Yu (ID: 17)
  • Paper 5: Incorporating the spiral of silence into opinion dynamics, Shir Mamia (ID: 20)
  • Paper 6: scPrisma infers, filters and enhances topological signals in single-cell data using spectral template matching, Jonathan Karin (ID: 25)
  • Paper 7: Graph Neural Network-Based Node Deployment for Throughput Enhancement, Yifei Yang (ID: 30)
  • Paper 8: GSP-Traffic Dataset: Graph Signal Processing Dataset Based on Traffic Simulation, Rui Kumagai (ID: 39)
  • Paper 9: Attack Graph Model for Cyber-Physical Power Systems Using Hybrid Deep Learning, Alfan Presekal (ID: 43)
  • Paper 10: Interpretable Diagnosis of Schizophrenia Using Graph-Based Brain Network Information Bottleneck, Tianzheng Hu (ID: 46)
  • Paper 11: Exploiting Variational Inequalities for Generalized Change Detection on Graphs, Juan F Florez (ID: 52)
  • Paper 12: Blind identification of overlapping communities from nodal observations, Ruben Wijnands (ID: 57)
  • Paper 13: Measuring Structure-Function Coupling Using Joint-modes of Multimodal Brain Networks, Sanjay Ghosh (ID: 62)
  • Paper 14: Autoregressive GNN for emulating Stormwater Drainage Flows, Alexander Garz n (ID: 63)
  • Paper 15: Faster Convergence with Less Communication: Broadcast-Based Subgraph Sampling for Decentralized Learning over Wireless Networks, Zheng Chen (ID: 71)
  • Paper 16: Data-driven Polytopic Output Synchronization from Noisy Data, Wenjie Liu (ID: 74)
  • Paper 17: A Graph Signal Processing Framework based on Graph Learning and Graph Neural Networks for Mental Workload Classification from EEG signals, Maria a Sarkis (ID: 76)
  • Paper 18: State Estimation in Water Distribution Systems using Diffusion on the Edge Space, Bulat Kerimov (ID: 82)
  • Paper 19: Neuro-GSTH: Quantitative analysis of spatiotemporal neural dynamics using geometric scattering and persistent homology, Dhananjay Bhaskar (ID: 85)
  • Paper 20: PET Image Representation and Reconstruction based on Graph Filter, Jingxin Zhang (ID: 41)