DEGAS Seminar

External homepage

computational engineering, finance, and science machine learning social and information networks optimization and control

Audience: Researchers in the discipline
Seminar series time: Wednesday 14:00-15:00 in your time zone, UTC
Organizers: Geert Leus, Dorina Thanou, Hoi-To Wai*
*contact for this listing

Registration link can be found in the external webpage.

Upcoming talks
Past talks
Your timeSpeakerTitle
WedDec 0416:00Renjie LiaoTBA
WedNov 2013:00Bastian Grossenbacher RieckVertex, Edge, Clique: What's in a Graph?
WedOct 0912:00Jhony GiraldoA Journey Through Graphs for Spatiotemporal Analysis
WedMay 2215:00Gal MishneLow Distortion Embedding with Bottom-up Manifold Learning
ThuApr 2513:00Elvin IsufiTBA
WedMar 1312:00Ron LevieTBA
WedFeb 2114:00Smita KrishnaswamyTBA
WedJan 1014:00Sundeep Prabhakar ChepuriTBA
WedDec 0614:00Xiaowen DongOn the stability of spectral graph filters and beyond: A topological perspective
WedApr 1213:00Hao ZhuTBA
WedMar 2913:00Gerald MatzGraphs for (multiple) data dichotomies
WedMar 1514:00Pierre BorgnatLearning distances for attributed graphs with optimal transport
WedFeb 2214:00Dimitri Van De VilleTBA
WedFeb 0114:00Francesca PariseTBA
WedJan 1814:00Stephan GünnemannTBA
WedDec 1414:00Haggai MaronSubgraph-based networks for expressive, efficient, and domain-independent graph learning
WedNov 3014:00Selin AviyenteSingle view and Multiview Signed Graph Learning: Applications to gene regulatory network inference
WedNov 1614:00Gonzalo MateosGraph adjacency spectral embeddings: Algorithmic advances and applications
WedNov 0214:00Sergio BarbarossaTopological signal processing and learning
WedOct 1913:00Panagiotis A. Traganitis, Georgios B. GiannakisLearning from Unreliable Labels via Crowdsourcing
ThuJun 0914:00Santiago SegarraPrincipled Simplicial Neural Networks for Trajectory Prediction
ThuMay 1914:00Usman KhanDistributed stochastic non-convex optimization: Optimal regimes and tradeoffs
ThuMay 0516:00Antonio OrtegaGraph Constructions for Machine Learning Applications: New Insights and Algorithms
ThuApr 1412:00Petar VeličkovićGraph Neural Networks are Dynamic Programmers
ThuMar 3113:00Alejandro RibeiroLearning by Transference in Large Graphs
ThuMar 1714:30Stefanie JegelkaLearning and Extrapolation in Graph Neural Networks
ThuMar 0314:00Steven SmithCausal Inference on Networks to Characterize Disinformation Narrative Propagation
ThuFeb 1714:00Alexander JungFederated Learning in Big Data over Networks
ThuJan 2713:00Michael BronsteinNeural diffusion PDEs, differential geometry, and graph neural networks
ThuJan 1314:00Peter BattagliaTBA
ThuDec 1615:30Jian TangGeometric Deep learning for Drug Discovery
Embed this schedule
Export series to