Welcome to the homepage of the Imperial College London machine learning reading group.
We meet Fridays at 13:00 in ~~Huxley 658~~ online on MS Teams.
Suggested papers can be found here.

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## 2020-2021

Date | Presenter | Paper | Author(s) | Notes |
---|---|---|---|---|

09/07/21 | Yanni Papandreou | On Mahalanobis distance in functional settings | Berrendero et al. | |

02/07/21 | Cris Salvi | On signature methods | ||

25/06/21 | Adam Howes | Small-area estimation with aggregated Gaussian processes | Adam Howes | |

18/06/21 | Juliette Unwin | Multilevel Monte Carlo methods | Michael B. Giles | |

11/06/21 | Michael Komodromos | Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap | Edwin Fong et al. | |

04/06/21 | Harrison Zhu | Multi-resolution Spatial Regression for Aggregated Data with an Application to Crop Yield Prediction | Harrison Zhu et al. | |

28/05/21 | Andrew Connell | Detecting changes in mean in the presence of time‐varying autocovariance | Euan T. McGonigle et al.. | |

21/05/21 | ||||

14/05/21 | George Wynne | CovNet: Covariance Networks for Functional Data on Multidimensional Domains | ||

07/05/21 | Isak Falk | |||

30/04/21 | Swapnil Mishra | |||

23/04/21 | Tim Wolock | |||

16/04/21 | Thomas Mellan | Gaussian Process Nowcasting: Application to COVID-19 Mortality Reporting | ||

09/04/21 | Tresnia Berah | Validated Variational Inference via Practical Posterior Error Bounds | ||

02/04/21 | break |
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26/03/21 | Harrison Zhu | Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm | ||

19/03/21 | Xenia Miscouridou | Modelling sparsity, heterogeneity, reciprocity and community structure in temporal interaction data | ||

26/02/21 | Michael | Gaussian Processes for Survival Analysis | Tamara Fernández | |

19/02/21 | ||||

12/02/21 | Jonathan | Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases | Ryan Steed & Aylin Caliskan | |

05/02/21 | Adriaan | Convolutional Gaussian Processes | Mark van der Wilk et al. | |

29/01/21 | Kate | Optimal Transport for Domain Adaptation | Nicolas Courty et al. | |

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04/12/20 | Jonathan | Bayesian Deep Ensembles via the Neural Tangent Kernel | Bobby He, Balaji Lakshminarayanan and Yee Whye Teh | |

27/11/20 | Kai | Training Agents using Upside-Down Reinforcement Learning | Rupesh Kumar Srivastava et al. | |

20/11/20 | James | Estimation of active pharmaceutical ingredients content using locally weighted partial least squares and statistical wavelength selection | Sanghong Kim et al. | |

13/11/20 | Daniel | GENNI: Visualising the Geometry of Equivalences for Neural Network Identifiability | Daniel Lengyel et al. | |

06/11/20 | Janith | Meta-Learning Symmetries by Reparameterization | Allan Zhou, Tom Knowles & Chelsea Finn | |

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23/10/20 | Kate | A continual learning survey: Defying forgetting in classification tasks | Matthias De Lange et al. | An Introduction to Continual Learning |

16/10/20 | Hans | JDINAC: joint density-based non-parametric differential interaction network analysis and classification using high-dimensional sparse omics data | Jiadong Ji et al. | |

09/10/20 | Joe | Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial Training | Joe Stacey et al. | |

02/10/20 |