BioInference

BioInference runs an annual conference that brings together mathematical biologists and statisticians to share ideas about best practices for inference across a range of application areas in mathematical biology.

The first conference was held in Oxford in 2022 and was possible through the generous funding received from the London Mathematical Society, the Heilbronn Institute and the Department of Computer Science, University of Oxford.

The 2022 lineup of talks and information for accessing and viewing posters is here: https://bioinference2022.github.io/

Inferring natural selection and allele age from allele frequency time series via exact simulation
Inferring natural selection and allele age from allele frequency time series via exact simulation
Bayesian calibration of differentiable simulators
Bayesian calibration of differentiable simulators
Closing remarks at BioInference 2023
Closing remarks at BioInference 2023
Inference in multivariate Wright-Fisher: Generalized Bayesian Inference with Signature Kernel Score
Inference in multivariate Wright-Fisher: Generalized Bayesian Inference with Signature Kernel Score
Can we control an epidemic in real-time with noisy data?
Can we control an epidemic in real-time with noisy data?
Neural assemblies uncovered by generative modeling explain whole-brain activity statistics
Neural assemblies uncovered by generative modeling explain whole-brain activity statistics
Parametrically Smoothened Likelihood Inference (PARSLI)
Parametrically Smoothened Likelihood Inference (PARSLI)
Inference of pathogen transmissibility during infectious disease outbreaks
Inference of pathogen transmissibility during infectious disease outbreaks
Statistical emulation for individual-based models of microbial community dynamics
Statistical emulation for individual-based models of microbial community dynamics
Training models with an ensemble of experimental designs to account for model discrepancy
Training models with an ensemble of experimental designs to account for model discrepancy
Opening remarks at BioInference 2023
Opening remarks at BioInference 2023
A Bayesian approach for estimating RNA velocity
A Bayesian approach for estimating RNA velocity
Simulating weak attacks in a new duplication-divergence model with gene loss
Simulating weak attacks in a new duplication-divergence model with gene loss
Bayesian computational analysis of cell division dynamics
Bayesian computational analysis of cell division dynamics
The development journey of a spatio-temporal infectious disease transmission model
The development journey of a spatio-temporal infectious disease transmission model
Amortized approach to non-linear mixed-effects modelling with neural density posterior estimation
Amortized approach to non-linear mixed-effects modelling with neural density posterior estimation
Rare event ABC-SMC^2
Rare event ABC-SMC^2
Heikki Haario - Statistical calibration of pattern formation models
Heikki Haario - Statistical calibration of pattern formation models
Aden Forrow - Measuring the accuracy of likelihood-free inference
Aden Forrow - Measuring the accuracy of likelihood-free inference
Jere Koskela - Nonreversible MCMC for latent phylogenetic trees
Jere Koskela - Nonreversible MCMC for latent phylogenetic trees
Kris Parag - Quantifying the relative information in noisy epidemic time series
Kris Parag - Quantifying the relative information in noisy epidemic time series
Michael Clerx - Four ways to fit an ion channel model
Michael Clerx - Four ways to fit an ion channel model
Rémi Bardenet - Monte Carlo methods based on repulsive point processes for generic expensive models
Rémi Bardenet - Monte Carlo methods based on repulsive point processes for generic expensive models
Alejandra D Herrera Reyes - Uncertainty and error in SARS-CoV-2 epidemiological parameters inferr...
Alejandra D Herrera Reyes - Uncertainty and error in SARS-CoV-2 epidemiological parameters inferr...
Discussion session - How best to share knowledge about inference methods
Discussion session - How best to share knowledge about inference methods
Ben Lambert - Prize giving and thanks at
Ben Lambert - Prize giving and thanks at "Inference for expensive systems in mathematical biology"
Solveig van der Vegt - Practical parameter identifiability applied to a model of autoimmune myoca...
Solveig van der Vegt - Practical parameter identifiability applied to a model of autoimmune myoca...
George Deligiannidis - Some results on MCMC algorithms for intractable likelihoods
George Deligiannidis - Some results on MCMC algorithms for intractable likelihoods
Marina Riabiz - Kernel Stein discrepancy minimization for MCMC thinning in cardiac electrophysiology
Marina Riabiz - Kernel Stein discrepancy minimization for MCMC thinning in cardiac electrophysiology
Richard Creswell - Using a posteriori error analysis to develop fast and low bias gradient-based ...
Richard Creswell - Using a posteriori error analysis to develop fast and low bias gradient-based ...