# Talks

**To be confirmed**

# Posters

ID | Presenter | Title |
---|---|---|

001 | Eliot Ayache (University of Bath) | Machine learning applications in High-Energy Time-Domain Astrophysics |

002 | Pasquale Cascarano (Università di Bologna) | Deep Plug-and-Play Gradient Method for Super-Resolution |

003 | Eric Baruch Gutierrez Castillo (University of Bath) | On Primal-Dual Algorithms for Nonsmooth Large-Scale Machine Learning |

004 | Dongdong Chen (University of Edinburgh) | Deep Plug-and-Play Network for Compressive MRF reconstruction |

005 | Maria Colomba Comes (University of Rome Tor Vergata) | Deep Prior for Cells Video Restoration |

006 | Jacob Deasy (University of Cambridge) | Closed-form differential entropy of a multi-layer perceptron variant |

007 | Margaret Duff (University of Bath) | Solving Inverse Imaging Problems with Generative |

008 | David Fernandes (University of Bath) | Unsupervised Learning with GPs and SDEs |

009 | Allen Hart (University of Bath) | Machine Learning Models |

010 | Allard Hendriksen (Centrum Wiskunde & Informatica (CWI), Amsterdam) | Noise2Inverse: Self-supervised deep convolutional denoising for linear inverse problems in imaging |

011 | Johannes Hertrich (TU Berlin) | Parseval Proximal Neural Networks |

012 | Gabriele Incorvaia (University of Manchester) | A deep learning application for Through-the-Wall Radar Imaging |

013 | Nicolas Keriven (CNRS, GIPSA-lab) | coordinate inter-building electricity demand |

014 | Youngkyu Lee (KAIST) | A parareal neural network emulating parallel-in-time algorithm |

015 | Peter Mathé (Weierstrass Institute) | Inverse learning in Hilbert scales |

016 | Janith Petangoda (Imperial College London) | Transfer Learning: An application of Foliations |

017 | Benedek Plosz (University of Bath) | Learning with unexplored priors systemises error propagation in Bayesian hierarchical modelling |

018 | Ilan Price (University of Oxford) | Trajectory growth through deep random ReLU networks |

019 | Abhishake Rastogi (University of Potsdam) | Regularization schemes for statistical inverse problems |

020 | Salvatore Danilo Riccio (Queen Mary University of London) | Robustness of Runge-Kutta networks against adversarial attacks |

021 | Paul Russell (University of Bath) | Learning to solve Rubik’s cube |

022 | Malena Sabaté (University of Bath) | Iteratively Reweighted Flexible Krylov methods for Sparse Reconstruction `Poster` `Video` |

023 | Silvester Sabathiel (NTNU Trondheim) | A computational model of learning to count in a multimodal, interactive environment |

024 | Ferdia Sherry (University of Cambridge) | Equivariant neural networks for inverse problems in imaging |

025 | Giuseppe Ughi (University of Oxford) | A Model-Based Derivative-Free Approach to Black-Box Adversarial Examples |

026 | Tiffany Vlaar (University of Edinburgh) | Partitioned Integrators for Thermodynamic Parameterization of NNs |

027 | Xiaoyu Wang (University of Cambridge) | Gradient-based training of non-smooth neural networks |

028 | Stefan Wild (Argonne National Laboratory) | Zero-order optimization for learning: How long can you wait? |

029 | Kelvin Shuangjian Zhang (ENS Paris) | Wasserstein control of mirror Langevin Monte Carlo |