publications

2025

  1. failure_flow.png
    Gradient Variance Reveals Failure Modes in Flow-Based Generative Models
    Teodora Reu, Sixtine Dromigny, Michael Bronstein, and Francisco Vargas
    Advances in Neural Information Processing Systems (NeurIPS 2025, Spotlight), 2025
    arXiv HTML

2024

  1. metric_flow.png
    Metric flow matching for smooth interpolations on the data manifold
    Kacper Kapuśniak, Peter Potaptchik, Teodora Reu, Leo Zhang, and 4 more authors
    Advances in Neural Information Processing Systems, 2024
    HTML
  2. cin.png
    Topological message passing for higher-order and long-range interactions
    Lorenzo Giusti, Teodora Reu, Francesco Ceccarelli, Cristian Bodnar, and 1 more author
    In 2024 International Joint Conference on Neural Networks (IJCNN), 2024
    HTML

2023

  1. diff.png
    Expressiveness Remarks for Denoising Diffusion Based Sampling
    Francisco Vargas, Teodora Reu, and Anna Kerekes
    In Fifth Symposium on Advances in Approximate Bayesian Inference, 2023
    HTML
  2. var_atte.png
    Rethinking Graph Topology Attentional and Variational Approaches
    Teodora Reu, and Pietro Liò
    2023
    PDF
  3. fisher.png
    An Exploration of Lottery Ticket Hypopthesis thorough Fisher Prunning
    Teodora Reu, Thomas Christie, Yumna Naqvi, and Matevz Matjasec
    Theory of Deep Learning Lecture, 2023
    PDF
  4. stable_star_systems.png
    Looking for Stable Celestial Systems Using Bayesian Optimisation
    Eirik Fladmark, Teodora Reu, and Laura Brinkholm Justesen
    arXiv preprint arXiv:2303.14835, 2023

2022

  1. breast_cancer.png
    Graph Neural Networks for Breast Cancer Data Integration
    Teodora Reu
    arXiv preprint arXiv:2211.15561, 2022