News archive
(for fresher news go to my start page)
- July 2022: I am the chair of the local organization for NORDSTAT 2023. Check out the event’s page at nordstat2023.org.
- July 2022: I am member of the scientific committee for the BayesComp 2023 satellite workshop “Bayesian computing without exact likelihoods” bayescomp2023.
- 27 June 2022: New paper: Guided sequential ABC schemes for intractable Bayesian models.
- June 2022: giving a talk at ISBA in Montreal on our Sequentially guided synthetic likelihoods paper on 28 June in the 1.30pm session. But there is also a poster here.
- May 2022: published on PLOS Comp. Biology: PEPSDI framework for Bayesian inference for mixed-effects stochastic models.
- 1 April 2022: here are slides from my talk at Maths department in Bristol on our PEPSDI work and generally SDE mixed-effects models.
- 8 February 2022: published on Bayesian Analysis, Sequentially guided MCMC proposals for synthetic likelihoods and correlated synthetic likelihoods.
- 24 September 2021: Samuel Wiqvist defends his PhD thesis.
- 4 July 2021: New paper “PEPSDI: Scalable and flexible inference framework for stochastic dynamic single-cell models”, bioRxiv.
- 2 July 2021: paper significantly updated “Stratified sampling and bootstrapping for approximate Bayesian computation”.
- 23 June -2 July 2021: I gave a talk at ISBA 2021 entitled “Guided sequential menthods for intractable Bayesian models”.
- 25 June 2021: significantly updated “Sequentially guided MCMC proposals for synthetic likelihoods and correlated synthetic likelihoods”, arxiv:2004.04558.
- 9 June 2021: significantly updated “Sequential neural posterior and likelihood approximation”, arxiv:2102.06522.
- 15 February 2021: New paper “Sequential neural posterior and likelihood approximation”, arxiv:2102.06522.
- 3 November 2020: revised “Adaptive MCMC for synthetic likelihoods and correlated synthetic likelihoods”, arxiv:2004.04558.
- 2 September 2020: PhD student Petar Jovanovski has started his position under my supervision; he will work on this project on simulation based inference.
PhD position with me! Apply by 1 June 2020- on 7 May 2020 I gave a zoom talk at the One World ABC Seminar. The video is available here.
- April 2020: New paper “Adaptive MCMC for synthetic likelihoods and correlated synthetic likelihoods”, arxiv:2004.04558.
- March 2020: revised “Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms.”, arXiv:1907.09851.
- January 2020: revised “Stratified sampling and bootstrapping for approximate Bayesian computation.”, arXiv:1905.07976.
- July 2019: New paper “Efficient inference for stochastic differential mixed-effects models using correlated particle pseudo-marginal algorithms.”, arXiv:1907.09851.
- May 2019: New revision of our accelerated MCMC paper.
- May 2019: New paper “Stratified sampling and resampling for approximate Bayesian computation.”, arXiv:1905.07976.
- April 2019: Paper accepted for the Proceedings of ICML, the International Conference on Machine Learning.
- February 2019: paper with Julie Forman accepted on JRSS series C.
- January 2019: New paper “Partially Exchangeable Networks and architectures for learning summary statistics in Approximate Bayesian Computation.”, arXiv:1901.10230.
- I will participate to ISBA 2018 in Edinburgh, including the satellite workshop on ABC, June 24-29.
- New paper with Samuel Wiqvist and Julie Forman: “Accelerating delayed-acceptance Markov chain Monte Carlo algorithms”, arXiv:1806.05982.
- May 2018: I moved from Lund University to Chalmers University of Technology and University of Gothenburg.