Publications

Drug-like antibodies with low immunogenicity in human panels designed with Latent-X2

Latent-X: An Atom-level Frontier Model for De Novo Protein Binder Design

Black-box Bayesian inference for agent-based models

Approximate Bayesian Computation with Path Signatures

PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis

Anoddpm: Anomaly detection with denoising diffusion probabilistic models using simplex noise

Denoising diffusion probabilistic models on so (3) for rotational alignment

Learning Multimodal VAEs through Mutual Supervision

Investigating the impact of model misspecification in neural simulation-based inference

Robust neural posterior estimation and statistical model criticism

Calibrating agent-based models to microdata with graph neural networks

Optimal scaling of random walk Metropolis algorithms using Bayesian large-sample asymptotics

Amortised likelihood-free inference for expensive time-series simulators with signatured ratio estimation

Approximate bayesian computation for panel data with signature maximum mean discrepancies

Capturing Label Characteristics in VAEs

Large-sample asymptotics of the pseudo-marginal method

Deep Signature Statistics for Likelihood-free Time-series Models

Neural odes for multi-state survival analysis

Generalized posteriors in approximate Bayesian computation

On Monte Carlo methods for intractable latent variable models

Bernoulli race particle filters

Estimating the density of ethnic minorities and aged people in Berlin: multivariate kernel density estimation applied to sensitive georeferenced administrative data protected via measurement error