Latest
- Four papers accepted at ICML 2025
- BayesComp satellite workshop
- Kernel Quantile Embeddings and Associated Probability Metrics
- ELLIS Scholar
- Nested Expectations with kernel Quadrature
- Cost-aware Simulation-based Inference
- Robust and Conjugate Spatio-Temporal Gaussian Processes
- Two papers accepted at AISTATS
- New role within the Bayesian Analysis journal.
- New role in the UCL Data-Intensive Science CDT
- Data Science Symposium on “Computational Statistics and Machine Learning in the Sciences"
- Royal Statistical Society membership
- On the Robustness of Kernel Goodness-of-Fit Tests
- Conditional Bayesian Quadrature
- Outlier-robust Kalman Filtering through Generalised Bayes
- Robust and Conjugate Gaussian Process Regression
- Meta-learning Control Variates: Variance Reduction with Limited Data
- Multilevel Bayesian Quadrature
- Vector-Valued Control Variates
- Bayesian Numerical Integration with Neural Networks
- Optimally-Weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference
- Robust and Scalable Bayesian Online Changepoint Detection
- Discrepancy-based Inference for Intractable Generative Models using Quasi-Monte Carlo
- Generalized Bayesian Inference for Discrete Intractable Likelihood
- Robust Generalised Bayesian Inference for Intractable Likelihoods
- A General Method for Calibrating Stochastic Radio Channel Models with Kernels
- Stein's Method Meets Computational Statistics: A Review of Some Recent Developments
- Towards Healing the Blindness of Score Matching
- Robust Bayesian inference for simulator-based models via the MMD posterior bootstrap
- Composite Goodness-of-fit Tests with Kernels
- Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization
- Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness
- Bayesian Probabilistic Numerical Integration with Tree-Based Models
- Minimum Stein Discrepancy Estimators