Seminars

We organise a number of seminars based on our common interests. You might also be interested in the seminar series in Statistics, Numerical Analysis, and Applied and Interdisciplinary Mathematics (AIMS).

Isotropic kernels with non-Euclidean metric,
Vangelis Evangelou (Bath)
Location: 3WN 3.7,  Time: 16:00, 08 Mar, 2023
Design and Recognition of Microgestures for Always-Available Input,
Adwait Sharma (Bath)
Location: 4W 1.7 Wolfson,  Time: 16:00, 22 Feb, 2023
Machine learning with probability generating functions,
Theodore Papamarkou (Manchester)
Location: CB 3.16,  Time: 16:00, 30 Nov, 2022
Transport maps in Bayesian inverse problems,
Sergey Dolgov (Bath)
Location: 4W 1.7 Wolfson,  Time: 16:30, 16 Nov, 2022
Algorithmic game theory, fixed point, and fair division,
Jie Zhang (Bath)
Location: 4W 1.7 Wolfson,  Time: 16:00, 16 Nov, 2022
Data-driven methods for imaging inverse problems: algorithms and theoretical guarantees,
Subhadip Mukherjee (Bath)
Location: 4W 1.7 Wolfson,  Time: 16:30, 02 Nov, 2022
Markov chain cubature for Bayesian inference,
James Foster (Bath)
Location: 4W 1.7 Wolfson,  Time: 16:00, 02 Nov, 2022
Challenges and improvements in optimization algorithms for machine learning,
Coralia Cartis (Oxford)
Location: Zoom,  Time: 12:15, 14 Jun, 2022
Random Primal-Dual Method with applications to Parallel MRI,
Eric Baruch Gutierrez (University of Bath)
Location: Wolfson,  Time: 12:15, 18 Mar, 2022 [url]
Regularising inverse imaging problems using generative deep learning models,
Margaret Duff (University of Bath)
Location: Wolfson,  Time: 12:15, 11 Mar, 2022 [url]
Bayesian Inverse Problems for NMR,
Michele Firmo (University of Bath)
Location: Wolfson,  Time: 12:15, 04 Mar, 2022 [url]
Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance),
Lisa Kreusser (Bath)
Location: Zoom,  Time: 12:15, 26 Nov, 2021 [url]
Deep Learning for convex optimisation (and beyond),
Sebastian Banert (Lund, Sweden)
Location: Zoom,  Time: 12:15, 29 Oct, 2021 [url]
A framework for analyzing variance reduced stochastic gradient methods and a new one,
Jingwei Liang (Shanghai Jiao Tong, China)
Location: Zoom,  Time: 12:15, 22 Oct, 2021 [url]
Dynamic inverse problems in spaces of measures with optimal-transport regularization,
Kristian Bredies (University of Graz, Austria)
Location: Wolfson,  Time: 12:15, 15 Oct, 2021 [url]
Rank-1 and rank-r lattices combined with operator splitting for time-dependent Schrödinger equations,
Yuya Suzuki (NTNU, Norway)
Location: MS Teams,  Time: 12:15, 30 Apr, 2021 [url]
Deep tensor decompositions for sampling from high-dimensional distributions,
Sergey Dolgov (Bath)
Location: MS Teams,  Time: 12:15, 23 Apr, 2021 [url]
High order numerical simulation of the underdamped Langevin diffusion,
James Foster (Oxford)
Location: MS Teams,  Time: 12:15, 16 Apr, 2021 [url]
Intrinsic subspaces of high-dimensional inverse problems and where to find them,
Tiangang Cui (Monash University, Australia)
Location: MS Teams,  Time: 12:15, 26 Mar, 2021 [url]
Synthetic data-driven methods for approximating high-dimensional Hamilton-Jacobi PDEs,
Dante Kalise (Nottingham)
Location: MS Teams,  Time: 12:15, 05 Mar, 2021 [url]
Continuum Limit for Lipschitz Learning on Graphs,
Leon Bungert (Erlangen, Germany)
Location: MS Teams,  Time: 12:15, 19 Feb, 2021 [url]
New Shapes, New Materials and New Processes,
Konrad Polthier (FU Berlin, Germany)
Location: MS Teams,  Time: 12:15, 27 Nov, 2020 [url]
Krylov Methods for Low-Rank Regularisation,
Silvia Gazzola (Bath)
Location: MS Teams,  Time: 12:15, 06 Nov, 2020 [url]
Learned SVD - Solving Inverse Problems via Hybrid Autoencoding,
Christoph Brune (Twente, Netherlands)
Location: MS Teams,  Time: 12:15, 30 Oct, 2020 [url]
Applications of Stochastic Differential Equations in Machine Learning,
Constantino Antonio García Martínez (University of Santiago de Compostela, Spain)
Location: MS Teams,  Time: 12:15, 23 Oct, 2020 [url]
Spectral methods for graph clustering, old and new,
Luca Zanetti (Bath)
Location: MS Teams,  Time: 12:15, 09 Oct, 2020 [url]
Deep Generative Models in Lattice Field Theories,
Pan Kessel (TU Berlin, Germany)
Location: MS Teams,  Time: 12:15, 02 Oct, 2020 [url]
Allen-Cahn and MBO on graphs,
Jeremy Budd (Delft, Netherlands)
Location: MS Teams,  Time: 12:15, 15 May, 2020 [url]
A fine(r)-grained perspective onto object interactions,
Dima Damen (University of Bristol)
Location: 1W 2.102,  Time: 11:15, 24 Mar, 2020
Hyperspectral tomography and reconstruction with the CCPi Core Imaging Library,
Jakob Jorgensen (University of Manchester)
Location: 4W 1.7 Wolfson,  Time: 12:15, 14 Feb, 2020
Models and Algorithms for Image Editing with Warping,
Ivor Simpson (University of Sussex)
Location: 3W 4.7,  Time: 14:15, 17 Jan, 2020
Inverse problems with imperfect forward operators and applications in image deblurring,
Yury Korolev (University of Cambridge)
Location: 4W 1.7 Wolfson,  Time: 13:15, 26 Nov, 2019 [url]
A forward-backward algorithm for reweighted procedures: Application to astro-imaging,
Audrey Repetti (Heriot-Watt, Edinburgh)
Location: 8W 2.27,  Time: 12:15, 08 Nov, 2019 [url]
How Many Labels Do You Need For Semi-Supervised Learning?,
Matt Thorpe (University of Manchester)
Location: 4W 1.7 Wolfson,  Time: 13:15, 22 Oct, 2019 [url]
Optimization Methods for Inverse Problems from Imaging,
Ke Chen (University of Liverpool)
Location: 4W 1.7 Wolfson,  Time: 13:15, 15 Oct, 2019 [url]
The geometry of first order methods and adaptive acceleration,
Clarice Poon (University of Bath)
Location: 4W 1.7 Wolfson,  Time: 12:15, 04 Oct, 2019 [url]
Assessing the performance in predicting terrorism in space and time using extreme gradient boosting and geostatistical models,
Andre Python (University of Oxford)
Location: CB 3.7,  Time: 14:15, 26 Mar, 2019 [url]
On Spectral Graph Clustering,
Carey E. Priebe (Johns Hopkins)
Location: CB 3.9,  Time: 14:15, 21 Mar, 2019 [url]
Bayesian inversion by deep learning with applications to tomography,
Ozan Oktem (Stockholm)
Location: 4W 1.7 Wolfson,  Time: 12:15, 01 Mar, 2019 [url]