Learning on Graphs Conference 2023

27 nov 2023

Learning on Graphs Conference - Keynote Speaker - Xiaowen Dong

Learning on Graphs Conference - Keynote Speaker - Xiaowen Dong

  • Vídeo  |   Español  |  76' 35''
    • Participante: Xiaowen Dong
      University of Oxford, Xiaowen Dong is an associate professor in the Department of Engineering Science at the University of Oxford, where he is a member of both the Machine Learning Research Group and the Oxford-Man Institute. Prior to joining Oxford, he was a postdoctoral associate in the MIT Media Lab, where he remains as a research affiliate, and received his PhD degree from the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. His main research interests concern signal processing and machine learning techniques for analysing network data, and their applications in social and economic sciences.
Learning on Graphs Conference - Selected Talks Monday

Learning on Graphs Conference - Selected Talks Monday

  • Vídeo  |   Español  |  108' 39''
    • Participante: Connor Clarkson
      Learning Types of Hierarchical Relationships on Complex Class Labelling Systems
    • Participante: Alberto Badias
      Structure-Preserving Graph Neural Networks
    • Participante: Christian Koke
      ResolvNet: A Graph Convolutional Network with multi-scale Consistency
    • Participante: Samuel Rey
      Robust Graph Neural Network based on Graph Denoising
    • Participante: Andrei Buciulea Vlas
      Learning Graphs and Simplicial Complexes from Data

28 nov 2023

Learning on Graphs Conference - Keynote Speaker -Reinhard Heckel

Learning on Graphs Conference - Keynote Speaker -Reinhard Heckel

  • Vídeo  |   Español  |  52' 32''
    • Participante: Reinhard Heckel
      Technical University of Munich, Reinhard Heckel is a Rudolf Moessbauer assistant professor in the Department of Computer Engineering at the Technical University of Munich, and an adjunct assistant professor at Rice University, where he was an assistant professor in the ECE department from 2017-2019. Before that, he was a postdoctoral researcher in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, and a researcher at the Cognitive Computing & Computational Sciences Department at IBM Research Zurich. He completed his PhD in electrical engineering in 2014 at ETH Zurich and was a visiting PhD student at the Statistics Department at Stanford University. Reinhard is working in the intersection of machine learning and signal/information processing with a current focus on deep networks for solving inverse problems, developing foundations and methods for machine learning, and DNA data storage.
Learning on Graphs Conference - Selected Talks Tuesday1

Learning on Graphs Conference - Selected Talks Tuesday1

  • Vídeo  |   Español  |  87' 15''
    • Participante: Jesús de la Fuente
      Towards a more inductive world for drug repurposing approaches
    • Participante: Asieh Abolpour Mofrad
      Leveraging Temporal Graph Neural Networks for Drug Repurposing Using Prescription Data in Norway
    • Participante: Óscar Méndez-Lucio
      A molecular foundation model for drug discovery based on molecular graphs
    • Participante: Uxía Veleiro
      GeNNius: An ultrafast drug-target interaction inference method based on graph neural networks
Learning on Graphs Conference - Selected Talks Tuesday2

Learning on Graphs Conference - Selected Talks Tuesday2

  • Vídeo  |   Español  |  81' 41''
    • Participante: Geert Leus
      A General Graph Convolution Theorem: Application to Dual Graph Inference
    • Participante: Iain Rolland
      Tensor completion using graph-based diffusion: a remote sensing image completion study
    • Participante: Víctor M Tenorio
      Recovering Missing Node Features with Local Structure-based Embeddings
    • Participante: Michelle Wan
      Completing Missing Air Quality Data with Graph-Based Techniques

29 nov 2023

Learning on Graphs Conference - Keynote Speaker - Ivan Dokmanić

Learning on Graphs Conference - Keynote Speaker - Ivan Dokmanić

  • Vídeo  |   Español  |  60' 44''
    • Participante: Ivan Dokmanić
      Associate Professor at the Department of Mathematics and Computer Science of the University of Basel.
Learning on Graphs Conference - Selected Talks Wednesday1

Learning on Graphs Conference - Selected Talks Wednesday1

  • Vídeo  |   Español  |  66' 23''
    • Participante: Guillermo Megías
      Using Graph Neural Networks to Predict Airport Congestion and Air Traffic Delays
    • Participante: Oscar Escudero
      Spatio-Temporal Graphs and GNN for Antimicrobial Multidrug Resistance Prediction in Intensive Care Unit
    • Participante: Carlos J. Rodríguez
      gMCSpy: Efficient and accurate computation of Genetic Minimal Cut Sets in Python
    • Participante: Oscar Llorente González
      Bayesian Graph Neural Networks, how to optimize a cellular network and provide confidence to our customers
Learning on Graphs Conference - Selected Talks Wednesday2

Learning on Graphs Conference - Selected Talks Wednesday2

  • Vídeo  |   Español  |  75' 31''
    • Participante: Manuele Leonelli
      Asymmetry-Labeled DAGs: Representation, Learning and Causal Reasoning
    • Participante: Christian Koke
      HoloNets: Spectral Convolutions do extend to Directed Graphs
    • Participante: Nathan Mankovich
      Graph-Based Dimensionality Reduction and Clustering for Earth and Life Sciences
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