One World Approximate Bayesian Computation (ABC) seminar

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statistics theory

Audience: Researchers in the topic
Seminar series times: No fixed schedule
Organizers: Massimiliano Tamborrino*, Julyan Arbel, Ritabrata Dutta, Richard Everitt, Paul Fearnhead, Michael Gutmann, Gael Martin, Antonietta Mira, Umberto Picchini, Dennis Prangle, Christian Robert, Judith Rousseau, Scott Sisson
*contact for this listing

Description: Approximation Bayesian computation, methods, and inference

The One World ABC seminar started in April 2020 as a way to gather members and disseminate results and innovation on ABC, likelihood free inference, PMCMC, etc., during those weeks and months under lockdown.

We are now ready to start Season 3 in September, with monthly seminars scheduled on the last Thursday of the month.

The interface for the seminars will be Zoom. Before each talk, a guest link will be mailed to the mailing list. Please register here listserv.csv.warwick.ac.uk/mailman/listinfo/abc_world_seminar to join the list.

Organisers: Julyan Arbel, Ritabrata Dutta, Richard Everitt, Paul Fearnhead, Michael Gutmann, Gael Martin, Antonietta Mira, Umberto Picchini, Dennis Prangle, Christian Robert, Judith Rousseau, Scott Sisson, Massimiliano Tamborrino

Upcoming talks
Past talks
Your timeSpeakerTitle
ThuJan 2713:30Rafael IzbickiTBA
ThuNov 2511:30Clara GrazianTBA
ThuOct 2810:30Michael Gutmann Publications TeachingTBA
ThuSep 3010:30Matias QuirozSpectral Subsampling MCMC for Stationary Multivariate Time Series
ThuMay 2710:30Veronika RockovaMetropolis-Hastings via Classification
ThuApr 2910:30Jakob MackeSimulation-based inference for neuroscience (and beyond)
ThuMar 2511:30Mijung ParkABCDP: Approximate Bayesian Computation with Differential Privacy
ThuDec 1011:30Matti ViholaOn the use of ABC-MCMC with inflated tolerance and post-correction
ThuNov 1211:30David NottMarginally-calibrated deep distributional regression
ThuOct 2911:30Agnieszka BorowskaGaussian process enhanced semi-automatic ABC for inference in a stochastic differential equation system for chemotaxis
ThuOct 1510:30David FrazierRobust and Efficient Approximate Bayesian Computation: A Minimum Distance Approach
ThuOct 0110:30Marko JärvenpääBatch simulations and uncertainty quantification in Gaussian process surrogate ABC
ThuSep 1710:30Flora Jay and Théophile SanchezDeep learning for population size history inference: design, comparison and combination with approximate Bayesian computation
ThuSep 0310:30Pierre-Alexandre Mattei and Samuel WiqvistPartially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation
ThuJul 1610:30Ruth BakerMulti-fidelity Approximate Bayesian computation
ThuJul 0210:30Chris Drovandimproving Bayesian Synthetic Likelihood via Transformations
ThuJun 1810:30Hien D. NguyenApproximate Bayesian computation via the energy statistic
ThuJun 0410:30Irene TubikanecSpectral density-based and measure-preserving ABC for partially observed diffusion processes. An illustration on Hamiltonian SDEs
ThuMay 2110:30Gael MartinFocused Bayesian prediction
ThuMay 0710:30Umberto PicchiniStratified sampling and bootstrapping for approximate Bayesian computation
ThuApr 2310:30Ivis Kerama and Richard EverittRare event ABC-SMC^2
ThuApr 0910:30Dennis PrangleDistilling importance sampling
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