Publications
Google Scholar Semantic Scholar UoE Paper RepoManuscripts
Refereed papers
Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational Families
Transactions on Machine Learning Research (TMLR), 2024
[url] [arxiv]
Transactions on Machine Learning Research (TMLR), 2024
[url] [arxiv]
Conditional Sampling of Variational Autoencoders via Iterated Approximate Ancestral Sampling
Transactions on Machine Learning Research, 2023
[url] [arxiv]
Transactions on Machine Learning Research, 2023
[url] [arxiv]
An Extendable Python Implementation of Robust Optimisation Monte Carlo
Journal of Statistical Software, 2023
[url] [arxiv]
Journal of Statistical Software, 2023
[url] [arxiv]
Is Learning Summary Statistics Necessary for Likelihood-free Inference?
Proceedings of the 40th International Conference on Machine Learning (ICML), 2023
[url]
Proceedings of the 40th International Conference on Machine Learning (ICML), 2023
[url]
Variational Gibbs Inference for Statistical Model Estimation from Incomplete Data
Journal of Machine Learning Research, 2023
[url] [arxiv]
Journal of Machine Learning Research, 2023
[url] [arxiv]
Estimating the Density Ratio between Distributions with High Discrepancy using Multinomial Logistic Regression
Transactions on Machine Learning Research, 2023
[url] [arxiv]
Transactions on Machine Learning Research, 2023
[url] [arxiv]
Bayesian Optimization with Informative Covariance
Transactions on Machine Learning Research, 2023
[url] [arxiv]
Transactions on Machine Learning Research, 2023
[url] [arxiv]
Enhanced gradient-based MCMC in discrete spaces
Transactions on Machine Learning Research, 2022
[url] [arxiv]
Transactions on Machine Learning Research, 2022
[url] [arxiv]
Inference and uncertainty quantification of stochastic gene expression via synthetic models
Journal of The Royal Society Interface, 2022
[url] [arxiv]
Journal of The Royal Society Interface, 2022
[url] [arxiv]
Systematic comparison of ranking aggregation methods for gene lists in experimental results
Bioinformatics, 2022
[url] [arxiv]
Bioinformatics, 2022
[url] [arxiv]
Bayesian Optimal Experimental Design for Simulator Models of Cognition
NeurIPS 2021 Workshop "AI for Science", 2021
[url] [arxiv]
NeurIPS 2021 Workshop "AI for Science", 2021
[url] [arxiv]
Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods
Proceedings of the Thirty-fifth Conference on Neural Information Processing Systems (NeuRIPS 2021), 2021
[url] [arxiv]
Proceedings of the Thirty-fifth Conference on Neural Information Processing Systems (NeuRIPS 2021), 2021
[url] [arxiv]
Neural Approximate Sufficient Statistics for Implicit Models
International Conference on Learning Representations (ICLR), 2021
[url] [arxiv]
International Conference on Learning Representations (ICLR), 2021
[url] [arxiv]
Sequential Bayesian Experimental Design for Implicit Models via Mutual Information
Bayesian Analysis, 2021
[url] [arxiv]
Bayesian Analysis, 2021
[url] [arxiv]
Parallel Gaussian process surrogate Bayesian inference with noisy likelihood evaluations
Bayesian Analysis, 2021
[url] [arxiv]
Bayesian Analysis, 2021
[url] [arxiv]
Telescoping Density-Ratio Estimation
Advances in Neural Information Processing Systems 34 (NeurIPS 2020), 2020
[url] [arxiv]
Advances in Neural Information Processing Systems 34 (NeurIPS 2020), 2020
[url] [arxiv]
Stir to Pour: Efficient Calibration of Liquid Properties for Pouring Actions
Proceedings of the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020), 2020
[url]
Proceedings of the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020), 2020
[url]
Robust Optimisation Monte Carlo
Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
[url] [arxiv]
Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
[url] [arxiv]
Molecular Patterns in Acute Pancreatitis Reflect Generalizable Endotypes of the Host Response to Systemic Injury in Humans
Annals of Surgery, 2020
[url] [arxiv]
Annals of Surgery, 2020
[url] [arxiv]
Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation
Proceedings of the 37th International Conference on Machine Learning (ICML), 2020
[url] [arxiv]
Proceedings of the 37th International Conference on Machine Learning (ICML), 2020
[url] [arxiv]
Generative Ratio Matching Networks
Proceedings of the International Conference on Learning Representations (ICLR), 2020
[url] [arxiv]
Proceedings of the International Conference on Learning Representations (ICLR), 2020
[url] [arxiv]
Genome-wide CRISPR screen Identifies Host Dependency Factors for Influenza A Virus Infection
Nature Communications, 2020
[url]
Nature Communications, 2020
[url]
Efficient Bayesian Experimental Design for Implicit Models
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
[url] [arxiv]
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
[url] [arxiv]
Bayesian inference of atomistic structure in functional materials
npj Computational Materials, 2019
[url] [arxiv]
npj Computational Materials, 2019
[url] [arxiv]
Variational Noise-Contrastive Estimation
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
[url] [arxiv]
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
[url] [arxiv]
Resolving outbreak dynamics using approximate Bayesian computation for stochastic birth-death models
Wellcome Open Research, 2019
[url] [arxiv]
Wellcome Open Research, 2019
[url] [arxiv]
Efficient acquisition rules for model-based approximate Bayesian computation
Bayesian Analysis, 2019
[url] [arxiv]
Bayesian Analysis, 2019
[url] [arxiv]
Adaptive Gaussian Copula ABC
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
[url] [arxiv]
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
[url] [arxiv]
Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria
The Annals of Applied Statistics, 2018
[url] [arxiv]
The Annals of Applied Statistics, 2018
[url] [arxiv]
Conditional Noise-Contrastive Estimation of Unnormalised Models
Proceedings of the 35th International Conference on Machine Learning (ICML), 2018
[url] [arxiv]
Proceedings of the 35th International Conference on Machine Learning (ICML), 2018
[url] [arxiv]
Bayesian inference of physiologically meaningful parameters from body sway measurements
Scientific Reports, 2017
[url]
Scientific Reports, 2017
[url]
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning
Advances in Neural Information Processing Systems 30 (NIPS 2017), 2017
[url] [arxiv]
Advances in Neural Information Processing Systems 30 (NIPS 2017), 2017
[url] [arxiv]
Simultaneous Estimation of Non-Gaussian Components and their Correlation Structure
Neural Computation, 2017
[url] [arxiv]
Neural Computation, 2017
[url] [arxiv]
Adaptable Pouring: Teaching Robots Not to Spill using Fast but Approximate Fluid Simulation
Proceedings of the 1st Annual Conference on Robot Learning (CoRL), 2017
[url]
Proceedings of the 1st Annual Conference on Robot Learning (CoRL), 2017
[url]
Fundamentals and Recent Developments in Approximate Bayesian Computation
Systematic Biology, 2017
[url]
Systematic Biology, 2017
[url]
Frequency-dependent selection in vaccine-associated pneumococcal population dynamics
Nature Ecology & Evolution, 2017
[url]
Nature Ecology & Evolution, 2017
[url]
The impact of host metapopulation structure on the population genetics of colonizing bacteria
Journal of Theoretical Biology, 2016
[url] [arxiv]
Journal of Theoretical Biology, 2016
[url] [arxiv]
On the identifiability of transmission dynamic models for infectious diseases
Genetics, 2016
[url] [arxiv]
Genetics, 2016
[url] [arxiv]
Bayesian optimization for likelihood-free inference of simulator-based statistical models
Journal of Machine Learning Research, 2016
[url] [arxiv]
Journal of Machine Learning Research, 2016
[url] [arxiv]
Recombination produces coherent bacterial species clusters in both core and accessory genomes
Microbial Genomics, 2015
[url]
Microbial Genomics, 2015
[url]
Estimating dependency structures for non-Gaussian components with linear and energy correlations
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), 2014
[url]
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), 2014
[url]
Direct learning of sparse changes in Markov networks by density ratio estimation
Neural Computation, 2014
[url] [arxiv]
Neural Computation, 2014
[url] [arxiv]
Spatio-chromatic adaptation via higher-order canonical correlation analysis of natural images
PLOS ONE, 2014
[url]
PLOS ONE, 2014
[url]
Correlated topographic analysis: estimating an ordering of correlated components
Machine Learning, 2013
[url]
Machine Learning, 2013
[url]
Direct learning of sparse changes in Markov networks by density ratio estimation
Machine Learning and Knowledge Discovery in Databases (ECML PKDD), 2013
[url]
Machine Learning and Knowledge Discovery in Databases (ECML PKDD), 2013
[url]
Estimation of unnormalized statistical models without numerical integration
Proceedings of the Workshop on Information Theoretic Methods in Science and Engineering, 2013
[url]
Proceedings of the Workshop on Information Theoretic Methods in Science and Engineering, 2013
[url]
Learning a selectivity--invariance--selectivity feature extraction architecture for images
Proceedings of the International Conference on Pattern Recognition (ICPR), 2012
[url]
Proceedings of the International Conference on Pattern Recognition (ICPR), 2012
[url]
Noise-contrastive estimation of unnormalized statistical models, with applications to natural image statistics
Journal of Machine Learning Research, 2012
[url]
Journal of Machine Learning Research, 2012
[url]
Complex-valued independent component analysis of natural images
Proceedings of the International Conference on Artificial Neural Networks (ICANN), 2011
[url]
Proceedings of the International Conference on Artificial Neural Networks (ICANN), 2011
[url]
Extracting coactivated features from multiple data sets
Proceedings of the International Conference on Artificial Neural Networks (ICANN), 2011
[url]
Proceedings of the International Conference on Artificial Neural Networks (ICANN), 2011
[url]
Bregman divergence as general framework to estimate unnormalized statistical models
Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2011
[url] [arxiv]
Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2011
[url] [arxiv]
A family of computationally efficient and simple estimators for unnormalized statistical models
Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2010
[url] [arxiv]
Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2010
[url] [arxiv]
Noise-contrastive estimation: A new estimation principle for unnormalized statistical models
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), 2010
[url]
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), 2010
[url]
Learning natural image structure with a horizonal product model
Proceedings on the International Conference on Independent Component Analysis and Signal Separation, 2009
[url]
Proceedings on the International Conference on Independent Component Analysis and Signal Separation, 2009
[url]
Learning reconstruction and prediction of natural stimuli by a population of spiking neurons
European Symposium on Artificial Neural Networks (ESANN), 2009
[url]
European Symposium on Artificial Neural Networks (ESANN), 2009
[url]
Learning features by contrasting natural images with noise
Proceedings of the International Conference on Artificial Neural Networks (ICANN), 2009
[url]
Proceedings of the International Conference on Artificial Neural Networks (ICANN), 2009
[url]
Learning encoding and decoding filters for data representation with a spiking neuron
Proceedings of the International Joint Conference on Neural Networks (IJCNN), 2008
[url]
Proceedings of the International Joint Conference on Neural Networks (IJCNN), 2008
[url]
Statistical models of images and early vision
Proceedings of the International and Interdisciplinary Conference on Adaptive Knowledge Representation and Reasoning (AKRR), 2005
[url]
Proceedings of the International and Interdisciplinary Conference on Adaptive Knowledge Representation and Reasoning (AKRR), 2005
[url]
Statistical model of natural stimuli predicts edge-like pooling of spatial frequency channels in V2
BMC Neuroscience, 2005
[url]
BMC Neuroscience, 2005
[url]
Workshop and other papers
Gradient-based Bayesian Experimental Design for Implicit Models using Mutual Information Lower Bounds
arXiv:2105.04379, 2021
[url] [arxiv]
arXiv:2105.04379, 2021
[url] [arxiv]
Bayesian Optimal Experimental Design for Simulator Models of Cognition
NeurIPS 2021 Workshop "AI for Science", 2021
[url] [arxiv]
NeurIPS 2021 Workshop "AI for Science", 2021
[url] [arxiv]
To Stir or Not to Stir: Online Estimation of Liquid Properties for Pouring Actions
Workshop on Learning and Inference in Robotics: Integrating Structure, Priors and Models, 2018
[url] [arxiv]
Workshop on Learning and Inference in Robotics: Integrating Structure, Priors and Models, 2018
[url] [arxiv]
Classification and Bayesian Optimization for Likelihood-Free Inference
arXiv:1502.05503, 2015
[url] [arxiv]
arXiv:1502.05503, 2015
[url] [arxiv]
Learning topographic representations for linearly correlated components
Workshop on Deep Learning and Unsupervised Feature Learning, NIPS, 2011
[url]
Workshop on Deep Learning and Unsupervised Feature Learning, NIPS, 2011
[url]
Learning spike-timings based representations of sensory stimuli with leaky integrate-and-fire neurons
BMC Neuroscience, 2009
[url]
BMC Neuroscience, 2009
[url]
Unsupervised learning by discriminating data from artificial noise
NIPS Workshop on Generative Discriminative Learning Interface, 2009
[url]
NIPS Workshop on Generative Discriminative Learning Interface, 2009
[url]
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