Archive for probabilistic numerics

hit by Brexit!

Posted in Statistics with tags , , , , , , , , , , , on August 17, 2022 by xi'an

After realising while at ISBA²² that Probabilistic Numerics,  the book of Philipp Heinig, Michael Osborne, and Hans Kersting, had appeared, I requested a copy for review in CHANCE from Cambridge University Press, which they kindly sent me. However, I received it with a 21€ bill for the novel VAT tax the EU has just (re)established for goods imported from outside the EU. From now on, I will have review books delivered to my Warwick address or sent from within the EU! (I have attempted to complain about paying VAT on free goods, but customs were not at all sympathetic!!!)

day two at ISBA 22

Posted in Mountains, pictures, Running, Statistics, Travel with tags , , , , , , , , , , , , , , , , , , , on June 30, 2022 by xi'an

Still woke up early too early, which let me go for a long run in Mont Royal (which felt almost immediately familiar from earlier runs at MCM 2017!) at dawn and at a pleasant temperature (but missed the top bagel bakery on the way back!). Skipped the morning plenary lectures to complete recommendation letters and finishing a paper submission. But had a terrific lunch with a good friend I had not seen in Covid-times, at a local branch of Kinton Ramen which I already enjoyed in Vancouver as my Airbnb was located on top of it.

I chaired the afternoon Bayesian computations session with Onur Teymur presenting the general spirit of his Neurips 21 paper on black box probabilistic numerics. Mentioning that a new textbook on the topic by Phillip Henning, Michael Osborne, and Hans Kersting had appeared today! The second talk was by Laura Bondi who discussed an ABC model choice approach to assess breast cancer screening. With enough missing data (out of 78051 women followed over 12 years) to lead to an intractable likelihood. Starting with vanilla ABC using 32 summaries and moving to our random forest approach. Unsurprisingly concluding with different top models, but not characterising the identifiability provided by the choice of the summaries. The third talk was by Ryan Chan (fresh Warwick PhD recipient), about a Fusion divide-and-conquer approach that avoids the approximation of earlier approaches. In particular he uses a clever accept-reject algorithm to generate a product of densities using the component densities. A nice trick that Murray explained to me while visiting in Paris lg ast month. (The approach appears to be parameterisation dependent.) The final talk was by Umberto Picchini and in a sort the synthetic likelihood mirror of Massi’s talk yesterday, in the sense of constructing a guided proposal relying on observed summaries. If not comparing both approaches on a given toy like the g-and-k distribution.

Savage Award session today at JSM

Posted in Kids, Statistics, Travel, University life with tags , , , , , , , , , , on August 3, 2020 by xi'an

Pleased to broadcast the JSM session dedicated to the 2020 Savage Award, taking place today at 13:00 ET (17:00 GMT), with two of the Savage nominees being former OxWaSP students (and Warwick PhD students). For those who have not registered for JSM, the talks are also available on Bayeslab. (As it happens, I was also a member of the committee this year, but do not think this could be deemed a CoI!)

112 Mon, 8/3/2020, 1:00 PM – 2:50 PM Virtual
Savage Award Session — Invited Papers
International Society for Bayesian Analysis (ISBA)
Organizer(s): Maria De Iorio, University College London
Chair(s): Maria De Iorio, University College London
1:05 PM Bayesian Dynamic Modeling and Forecasting of Count Time Series
Lindsay Berry, Berry Consultants
1:30 PM Machine Learning Using Approximate Inference: Variational and Sequential Monte Carlo Methods
Christian Andersson Naesseth, Columbia University
1:55 PM Recent Advances in Bayesian Probabilistic Numerical Integration
Francois-Xavier Briol, University College London
2:20 PM Factor regression for dimensionality reduction and data integration techniques with applications to cancer data
Alejandra Avalos Pacheco, Harvard Medical School
2:45 PM Floor Discussion

séminaire P de S

Posted in Books, pictures, Statistics, University life with tags , , , , , , , , , on February 18, 2020 by xi'an

As I was in Paris and free for the occasion (!), I attended the Paris Statistics seminar this afternoon, in the Latin Quarter. With a first talk by Kweku Abraham on Bayesian inverse problems set a prior on the quantity of interest, γ, rather than its transform G(γ), observed with noise. Always perturbed by the juggling of different distances, like L² versus Kullback-Leibler, in non-parametric frameworks. Reminding me of probabilistic numerics, at least in the framework, since the crux of the talk was 100% about convergence. And a second talk by Leanaïc Chizat on convex neural networks corresponding to an infinite number of neurons, with surprising properties, including implicit bias. And a third talk by Anne Sabourin on PCA for extremes. Which assumed very little on the model but more on the geometry of the distribution, like extremes being concentrated on a subspace. As I was rather tired from an intense week at Warwick, and after a weekend of reading grant applications and Biometrika submissions (!), my foggy brain kept switching to these proposals, trying to make connections with the talks, not completely inappropriately in two cases out of three. (I am afraid the same may happen tomorrow at our probability seminar on computer-based proofs!)

Bayesian probabilistic numerical methods

Posted in Books, pictures, Statistics, University life with tags , , , , , , on December 5, 2019 by xi'an

“…in isolation, the error of a numerical method can often be studied and understood, but when composed into a pipeline the resulting error structure maybe non-trivial and its analysis becomes more difficult. The real power of probabilistic numerics lies in its application to pipelines of numerical methods, where the probabilistic formulation permits analysis of variance (ANOVA) to understand the contribution of each discretisation to the overall numerical error.”

Jon Cockayne (Warwick), Chris Oates (formerly Warwick), T.J. Sullivan, and Mark Girolami (formerly Warwick) got their survey on Bayesian probabilistic numerical methods in the SIAM (Society for Industrial and Applied Mathematics) Review, which is quite a feat given the non-statistical flavour of the journal (although Art Owen is now one of the editors of the review). As already reported in some posts on the ‘Og, the concept relies on the construction of a prior measure over a set of potential solutions, and numerical methods are assessed against the associated posterior measure. Not only is this framework more compelling in a conceptual sense, but it also leads to novel probabilistic numerical methods managing to solve quite challenging numerical tasks. Congrats to the authors!

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