Zobrazeno 1 - 10
of 188
pro vyhledávání: '"P, Gabrie"'
Over the past few years, several approaches utilizing score-based diffusion have been proposed to sample from probability distributions, that is without having access to exact samples and relying solely on evaluations of unnormalized densities. The r
Externí odkaz:
http://arxiv.org/abs/2410.19449
While deep learning has expanded the possibilities for highly expressive variational families, the practical benefits of these tools for variational inference (VI) are often limited by the minimization of the traditional Kullback-Leibler objective, w
Externí odkaz:
http://arxiv.org/abs/2410.13300
We propose a sampling algorithm relying on a collective variable (CV) of mid-size dimension modelled by a normalizing flow and using non-equilibrium dynamics to propose full configurational moves from the proposition of a refreshed value of the CV ma
Externí odkaz:
http://arxiv.org/abs/2406.01524
We consider the problem of sampling a high dimensional multimodal target probability measure. We assume that a good proposal kernel to move only a subset of the degrees of freedoms (also known as collective variables) is known a priori. This proposal
Externí odkaz:
http://arxiv.org/abs/2405.18160
Building upon score-based learning, new interest in stochastic localization techniques has recently emerged. In these models, one seeks to noise a sample from the data distribution through a stochastic process, called observation process, and progres
Externí odkaz:
http://arxiv.org/abs/2402.10758
Extracting consistent statistics between relevant free-energy minima of a molecular system is essential for physics, chemistry and biology. Molecular dynamics (MD) simulations can aid in this task but are computationally expensive, especially for sys
Externí odkaz:
http://arxiv.org/abs/2401.16487
Energy-based models (EBMs) are versatile density estimation models that directly parameterize an unnormalized log density. Although very flexible, EBMs lack a specified normalization constant of the model, making the likelihood of the model computati
Externí odkaz:
http://arxiv.org/abs/2306.00684
Artificial networks have been studied through the prism of statistical mechanics as disordered systems since the 80s, starting from the simple models of Hopfield's associative memory and the single-neuron perceptron classifier. Assuming data is gener
Externí odkaz:
http://arxiv.org/abs/2304.06636
Autor:
Johnny Kenth, Elizabeth Maughan, Colin R Butler, Jasleen Gabrie, Maral Rouhani, Benjamin Silver, Olumide K Ogunbiyi, Stuart Wilkinson, Reema Nandi, Robert Walker, Nagarajan Muthialu, Simon Jones, Richard Hewitt, Iain A Bruce
Publikováno v:
Orphanet Journal of Rare Diseases, Vol 19, Iss 1, Pp 1-16 (2024)
Abstract Background Mucopolysaccharidosis (MPS) type IVA is a rare lysosomal storage disorder caused by aberrations of the N-acetyl-galactosamine-6-sulfatase (GALNS) enzyme. MPS IVA is associated with a wide gamut of respiratory and airway disorders
Externí odkaz:
https://doaj.org/article/7834c7ec13d8457c9faf74eb47a221cb
Transport maps can ease the sampling of distributions with non-trivial geometries by transforming them into distributions that are easier to handle. The potential of this approach has risen with the development of Normalizing Flows (NF) which are map
Externí odkaz:
http://arxiv.org/abs/2302.04763