Archive for dawn
Dawn on Wear [jatp]
Posted in pictures, Running, Travel, University life with tags #ERCSyG, dawn, Durham, Durham university, ERC, jatp, Low Burnhall Woodlands, Northumberland, Oceanerc, River Browney, River Wear, sunrise, The North, trail running, Woodland Trust on September 4, 2026 by xi'an
settimana scorsa a Venezia
Posted in pictures, Running, Travel, University life with tags airport, Cannaregio Canal, chemical complex, dawn, Italia, laguna, Marco Polo, Mestre, moonset, plane trip, Porto Marghera, Punta della Liberta, Serinissima, sunrise, supermoon, Università Ca' Foscari Venezia, Venezia, Venice, visiting position on April 21, 2026 by xi'an
likelihood-free posterior density learning at OWABI [30 April, 1pm GMT+1, 2pm CEST, 8am EST]
Posted in pictures, Running, Statistics, Travel, University life with tags ABC, Approximate Bayesian computation, Columbus, Coventry, dawn, deep learning, generative model, intractable likelihood, KASPE, Kenilworth, likelihood-free inference, Ohio State University, OWABI, posterior distribution, simulation-based inference, University of Warwick, webinar on April 17, 2026 by xi'an
The next OWABI webinar will take place on 30 April, at 1pm Coventry time (2pm in Paris, 8am in Columbus, Ohio) and will feature
Oksana A. Chkrebtii (Ohio State University)
Likelihood-free Posterior Density Learning for Uncertainty Quantification in Inference Problems
Generative models and those with computationally intractable likelihoods are widely used to describe complex systems in the natural sciences, social sciences, and engineering. Fitting these models to data requires likelihood-free inference methods that explore the parameter space without explicit likelihood evaluations, relying instead on sequential simulation, which comes at the cost of computational efficiency and extensive tuning. We develop an alternative framework called kernel-adaptive synthetic posterior estimation (KASPE) that uses deep learning to directly reconstruct the mapping between the observed data and a finite-dimensional parametric representation of the posterior distribution, trained on a large number of simulated datasets. We provide theoretical justification for KASPE and a formal connection to the likelihood-based approach of expectation propagation. Simulation experiments demonstrate KASPE’s flexibility and performance relative to existing likelihood-free methods including approximate Bayesian computation in challenging inferential settings involving posteriors with heavy tails, multiple local modes, and over the parameters of a nonlinear dynamical system.
sole della libertà [jatp]
Posted in pictures, Running, Travel with tags Bayesian conference, dawn, Fusion 2024, ISBA 2024, Italia, jatp, laguna, Ponte della Libertà, red shift, sunset, train, Università Ca' Foscari Venezia, Venezia, Venice on July 26, 2024 by xi'an
Golden dawn [jatp]
Posted in Statistics with tags air quality, British Columbia, Canada, Columbia River, dawn, forest fires, Golden, smoke, sunrise, wildfire on August 12, 2023 by xi'an
