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Partially Exchangea...
Partially Exchangeable Networks and architectures for learning summary statistics in Approximate Bayesian Computation
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- Wiqvist, Samuel (författare)
- Lund University,Lunds universitet,Matematisk statistik,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Mathematical Statistics,Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH
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- Mattei, Pierre-Alexandre (författare)
- IT-Universitetet i Kobenhavn,IT University of Copenhagen
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- Picchini, Umberto (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper, Tillämpad matematik och statistik,Department of Mathematical Sciences, Applied Mathematics and Statistics,University of Gothenburg,Chalmers tekniska högskola,Chalmers University of Technology
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- Frellsen, Jes (författare)
- IT-Universitetet i Kobenhavn,IT University of Copenhagen
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(creator_code:org_t)
- PMLR, 2019
- 2019
- Engelska.
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Ingår i: Proceedings of the 36th International Conference on Machine Learning. - : PMLR. ; 2019-June, s. 11795-11804
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Abstract
Ämnesord
Stäng
- We present a novel family of deep neural architectures, named partially exchangeable networks (PENs) that leverage probabilistic symmetries. By design, PENs are invariant to block-switch transformations, which characterize the partial exchangeability properties of conditionally Markovian processes. Moreover, we show that any block-switch invariant function has a PEN-like representation. The DeepSets architecture is a special case of PEN and we can therefore also target fully exchangeable data. We employ PENs to learn summary statistics in approximate Bayesian computation (ABC). When comparing PENs to previous deep learning methods for learning summary statistics, our results are highly competitive, both considering time series and static models. Indeed, PENs provide more reliable posterior samples even when using less training data.
Ämnesord
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
Nyckelord
- deep learning; intractable likelihood; Markov data; time series
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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