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.
Programme
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
Research talks
- Ed Davis – Universal Dynamic Network Embedding – How to Comprehend Changes in 20,000 Dimensions
- 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
- Hannah Sansford – Implications of sparsity and high triangle density for graph representation learning
- Michael Whitehouse – Consistent and fast inference in compartmental models of epidemics via Poisson Approximate Likelihoods
- 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.
Attendees
Attendees included academics associated with Compass from across the University of Bristol. Our external attendees were invited from the following partner organisations.
Adarga
Advai
Alan Turing Institute
Allianz Personal
AWE
British Telecom
CheckRisk LLP
COVID-19 Actuaries Response Group
Financial Times
GSK
Improbable
Infinitesima
International Livestock Research Institute
LV= General Insurance
Met Office
NVIDIA
TGE Data Science
Trilateral Research
UK Health Security Agency
