Our first Compass Conference was held on Tuesday 13th September 2022, hosted in the newly refurbished Fry Building, home to the School of Mathematics.
The conference was a celebratory showcase of the achievements of our students, supervisory teams, and collaborations with industrial partners. Attendees were invited from a diverse range of organisations outside of academia as well as academic colleagues from across the University of Bristol.
- Ed Davis – Universal Dynamic Network Embedding – How to Comprehend Changes in 20,000 Dimensions (download slides)
- Ettore Fincato – Spectral analysis of the Gibbs sampler with the concept of conductance
- Alexander Modell – Network community detection under degree heterogeneity: spectral clustering with the random walk Laplacian (download slides)
- Hannah Sansford – Implications of sparsity and high triangle density for graph representation learning (download slides)
- Michael Whitehouse – Consistent and fast inference in compartmental models of epidemics via Poisson Approximate Likelihoods (download slides)
- Alessio Zakaria – Your Favourite Optimizer may not Converge: Click here to see more
Special guest lecture
John Burn-Murdoch, Chief Data Reporter at the Financial Times.
Making charts that make an impact: An exploration of what makes data visualisation effective as a means of communication, drawing on the latest scientific research, plus John’s experiences from visualising the pandemic.
Lightning talks: 3 min presentations from Compass PhD students
- Mauro Camara Escudero: Approximate Manifold Sampling
- Doug Corbin: Partitioned Polynomial Thompson Sampling for Contextual Multi-Armed Bandits.
- Dom Owens: FNETS: An R Package for Network Analysis and Forecasting of High-Dimensional Time Series with Factor-Adjusted Vector Autoregressive Models
- Jake Spiteri: A non-parametric method for state-space models
- Daniel Williams: Kernelised Stein Discrepancies for Truncated Probability Density Estimation
- Conor Crilly: Efficient Emulation of a Radionuclide Transport Model
- Annie Gray: Discovering latent topology and geometry in data: a law of large dimension
- Conor Newton: Mutli-Agent Multi-Armed Bandits
- Jack Simons: Variational Likelihood-Free Gradient Descent
- Anthony Stephenson: Provably Reliable Large-Scale Sampling from Gaussian Processes
- Dan Ward: Robust Neural Posterior Estimation
- Shannon Williams: Sampling Schemes for Volcanic Ash Dispersion Hazard Assessment
- Dominic Broadbent: Bayesian Coresets Versus the Laplace Approximation
- Emerald Dilworth: Using Web Data and Network Embedding to Detect Spatial Relationships
- Ettore Fincato: Markov state modelling and Gibbs sampling
- Josh Givens: DRE and NP Classification with Missing Data
- Ben Griffiths: Faster Model Fitting for Quantile Additive Models
- Tennessee Hickling: Flexible Tails for Normalising Flows
- Daniel Milner: When Does Market Access Improve Smallholder Nutrition? A Multilevel Analysis
- Edward Milsom: Deep Kernel Machines
Attendees included academics associated with Compass from across the University of Bristol. Our external attendees were invited from the following partner organisations.
Alan Turing Institute
COVID-19 Actuaries Response Group
International Livestock Research Institute
LV= General Insurance
TGE Data Science
UK Health Security Agency