Archive for EDF
Rumpe Cuou, Sormiou, in an electricity ad
Posted in Mountains, pictures, Travel with tags advertising, big wall, CIRM, climbing, CO2, EDF, Electricité de France, electricity, greenwashing, Le Monde, Luminy, Marseille, massif des Calanques, mountain guide, Rumpe Cuou, Sormiou on July 15, 2025 by xi'an
more than mostly MC
Posted in Kids, pictures, Statistics, Travel, University life with tags casino, cross-entropy method, diffusion sampler, EDF, Gaussian mixture, group picture, importance sampling, modes of a mixture, Monaco, Monte Carlo, Monte-Carlo casino, multimodality, nuclear energy, nuclear plant, ODE, Paris, PariSanté campus, PDEs, PDMP, piecewise deterministic, rare events, SDEs, simulated annealing on December 27, 2024 by xi'an
The session of last Friday (and last one of 2024!) proved most interesting, with two (fully) Monte Carlo talks. The first one by Louis Grenioux was about an improvement on diffusion sampler, following a recent arXival by Maxime Noble and co-authors. Which brought me back to the long-standing multimodal challenge in Monte Carlo methods. When all modes of a target distribution are known, even roughly, this is not much of an issue since samplers can be arm-bent into visiting all these modes. But the problem becomes much harder when the location and a fortiori the number of modes are not known. The paper aims at adapting diffusion samplers towards a better exploration of the modes, albeit their location is known. Otherwise, using MCMC as a starting (reference) distribution would risk missing some of them. Which also explains why the authors can rely on the classical Gaussian mixtures proposal as a cheap substitute to neural networks (EBM). Since, within diffusion models, both intermediary distributions and their scores are intractable, they also introduce a variational parametric approximation that can be optimised.
The second talk was given by Guillaume Chennetier, in connection with his recent PhD thesis, developing a form of X-entropy sampling for rare events. As in nuclear plant major accidents. It took me a while to realise that PDMPs were not used as a simulation tool, as in the zigzag sampler and its avatars, The proposal involved creating a graph structure on the space of PDMP trajectories and designing the optimal importance process (yes, the one with zero variance!) using so-called committor functions that modify jump intensity and kernel, in a sequential way reminiscent of X-entropy. The approach recycles past trajectories as Monte Carlo elements if missing an adaptive mixture importance sampling (AMIS!) version that would bring more stability. The talk also included an interesting pointer to the availability of the distribution of the PDMP path, thus treated as a likelihood. (!). The signage at the entrance of the Monte-Carlo (mind the hyphen!) casino also made an appearance, reminding me of our memorable group picture on the same spot, eons ago! (But not of whom took the picture!)
clustering dynamical networks
Posted in pictures, Statistics, University life with tags CREST, EDF, EM algorithm, gas holder, graphs, hidden networks, Paris-Saclay campus, random graphs, SFDS, social networks, variational Bayes methods on June 5, 2018 by xi'an
Yesterday I attended a presentation by Catherine Matias on dynamic graph structures, as she was giving a plenary talk at the 50th French statistical meeting, conveniently located a few blocks away from my office at ENSAE-CREST. In the nicely futuristic buildings of the EDF campus, which are supposed to represent cogs according to the architect, but which remind me more of these gas holders so common in the UK, at least in the past! (The E of EDF stands for electricity, but the original public company handled both gas and electricity.) This was primarily a survey of the field, which is much more diverse and multifaceted than I realised, even though I saw some recent developments by Antonietta Mira and her co-authors, as well as refereed a thesis on temporal networks at Ca’Foscari by Matteo Iacopini, which defence I will attend in early July. The difficulty in the approaches covered by Catherine stands with the amount and complexity of the latent variables induced by the models superimposed on the data. In her paper with Christophe Ambroise, she followed a variational EM approach. From the spectator perspective that is mine, I wondered at using ABC instead, which is presumably costly when the data size grows in space or in time. And at using tensor structures as in Mateo’s thesis. This reminded me as well of Luke Bornn’s modelling of basketball games following each player in real time throughout the game. (Which does not prevent the existence of latent variables.) But more vaguely and speculatively I also wonder at the meaning of the chosen models, which try to represent “everything” in the observed process, which seems doomed from the start given the heterogeneity of the data. While reaching my Keynesian pessimistic low- point, which happens rather quickly!, one could hope for projection techniques, towards reducing the dimension of the data of interest and of the parameter required by the model.
