DEGAS Seminar

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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 time			Speaker	Title
Wed	Jan 22	15:00	Yanning Shen	Demystifying and Mitigating Unfairness for Learning over Graphs

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Your time			Speaker	Title
Wed	Dec 04	16:00	Renjie Liao	TBA
Wed	Nov 20	13:00	Bastian Grossenbacher Rieck	Vertex, Edge, Clique: What's in a Graph?
Wed	Oct 09	12:00	Jhony Giraldo	A Journey Through Graphs for Spatiotemporal Analysis
Wed	May 22	15:00	Gal Mishne	Low Distortion Embedding with Bottom-up Manifold Learning
Thu	Apr 25	13:00	Elvin Isufi	TBA
Wed	Mar 13	12:00	Ron Levie	TBA
Wed	Feb 21	14:00	Smita Krishnaswamy	TBA
Wed	Jan 10	14:00	Sundeep Prabhakar Chepuri	TBA
Wed	Dec 06	14:00	Xiaowen Dong	On the stability of spectral graph filters and beyond: A topological perspective
Wed	Apr 12	13:00	Hao Zhu	TBA
Wed	Mar 29	13:00	Gerald Matz	Graphs for (multiple) data dichotomies
Wed	Mar 15	14:00	Pierre Borgnat	Learning distances for attributed graphs with optimal transport
Wed	Feb 22	14:00	Dimitri Van De Ville	TBA
Wed	Feb 01	14:00	Francesca Parise	TBA
Wed	Jan 18	14:00	Stephan Günnemann	TBA
Wed	Dec 14	14:00	Haggai Maron	Subgraph-based networks for expressive, efficient, and domain-independent graph learning
Wed	Nov 30	14:00	Selin Aviyente	Single view and Multiview Signed Graph Learning: Applications to gene regulatory network inference
Wed	Nov 16	14:00	Gonzalo Mateos	Graph adjacency spectral embeddings: Algorithmic advances and applications
Wed	Nov 02	14:00	Sergio Barbarossa	Topological signal processing and learning
Wed	Oct 19	13:00	Panagiotis A. Traganitis, Georgios B. Giannakis	Learning from Unreliable Labels via Crowdsourcing
Thu	Jun 09	14:00	Santiago Segarra	Principled Simplicial Neural Networks for Trajectory Prediction
Thu	May 19	14:00	Usman Khan	Distributed stochastic non-convex optimization: Optimal regimes and tradeoffs
Thu	May 05	16:00	Antonio Ortega	Graph Constructions for Machine Learning Applications: New Insights and Algorithms
Thu	Apr 14	12:00	Petar Veličković	Graph Neural Networks are Dynamic Programmers
Thu	Mar 31	13:00	Alejandro Ribeiro	Learning by Transference in Large Graphs
Thu	Mar 17	14:30	Stefanie Jegelka	Learning and Extrapolation in Graph Neural Networks
Thu	Mar 03	14:00	Steven Smith	Causal Inference on Networks to Characterize Disinformation Narrative Propagation
Thu	Feb 17	14:00	Alexander Jung	Federated Learning in Big Data over Networks
Thu	Jan 27	13:00	Michael Bronstein	Neural diffusion PDEs, differential geometry, and graph neural networks
Thu	Jan 13	14:00	Peter Battaglia	TBA
Thu	Dec 16	15:30	Jian Tang	Geometric Deep learning for Drug Discovery

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