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Each training step for a variational autoencoder (VAE) requires us to sample from the approximate posterior, so we usually choose simple (e.g. factorised) approximate posteriors in which sampling is an efficient computation that fully…

Machine Learning · Statistics 2018-05-29 Laurence Aitchison , Vincent Adam , Srinivas C. Turaga

Encounter-based models of diffusion provide a probabilistic framework for analyzing the effects of a partially absorbing reactive surface, in which the probability of absorption depends upon the amount of surface-particle contact time.…

Statistical Mechanics · Physics 2023-07-05 Paul C Bressloff

This paper proposes a novel diffusion-based posterior sampling method within a plug-and-play (PnP) framework. Our approach constructs a probability transport from an easy-to-sample terminal distribution to the target posterior, using a…

Machine Learning · Statistics 2025-12-10 Jinyuan Chang , Chenguang Duan , Yuling Jiao , Ruoxuan Li , Jerry Zhijian Yang , Cheng Yuan

We investigate the convergence properties of popular data-augmentation samplers for Bayesian probit regression. Leveraging recent results on Gibbs samplers for log-concave targets, we provide simple and explicit non-asymptotic bounds on the…

Computation · Statistics 2025-05-21 Filippo Ascolani , Giacomo Zanella

This work is concerned with the development of a space-time adaptive numerical method, based on a rigorous a posteriori error bound, for a semilinear convection-diffusion problem which may exhibit blow-up in finite time. More specifically,…

Numerical Analysis · Mathematics 2015-02-12 Andrea Cangiani , Emmanuil H. Georgoulis , Irene Kyza , Stephen Metcalfe

We compute the limiting distributions of the lengths of the longest monotone subsequences of random (signed) involutions with or without conditions on the number of fixed points (and negated points) as the sizes of the involutions tend to…

Combinatorics · Mathematics 2007-05-23 Jinho Baik , Eric M. Rains

We show that Set Cover on instances with $N$ elements cannot be approximated within $(1-\gamma)\ln N$-factor in time exp($N^{\gamma-\delta})$, for any $0 < \gamma < 1$ and any $\delta > 0$, assuming the Exponential Time Hypothesis. This…

Data Structures and Algorithms · Computer Science 2020-08-13 Marek Cygan , Magnús M. Halldórsson , Guy Kortsarz

The regulation of a gene depends on the binding of transcription factors to specific sites located in the regulatory region of the gene. The generation of these binding sites and of cooperativity between them are essential building blocks…

Statistical Mechanics · Physics 2007-05-23 Johannes Berg , Stana Willmann , Michael Lässig

In this paper we treat some fractal and statistical features of the DNA sequences. First, a fractal record model of DNA sequence is proposed by mapping DNA sequences to integer sequences, followed by R/S analysis of the model and…

Biological Physics · Physics 2018-01-17 Zu-Guo Yu , Guo-Yi Chen

Recent works proposed test-time alignment methods that rely on a small aligned model as a proxy that guides the generation of a larger base (unaligned) model. The implicit reward approach skews the large model distribution, whereas the…

Computation and Language · Computer Science 2026-04-21 Ayoub Hammal , Pierre Zweigenbaum , Caio Corro

The aim in model order reduction is to approximate an input-output map described by a large-scale dynamical system with a low-dimensional and cheaper-to-evaluate reduced order model. While high fidelity can be achieved by a variety of…

Dynamical Systems · Mathematics 2023-01-04 Björn Liljegren-Sailer

Genetic and comparative genomic studies indicate that extant genomes are more properly considered to be a fusion product of random mutations over generations and genomic material transfers between individuals of different lineages. This has…

Quantitative Methods · Quantitative Biology 2018-01-16 Andreas D. M. Gunawan , Bingxin Lu , Louxin Zhang

We revisit the classical problem of universal prediction of stochastic sequences with a finite time horizon $T$ known to the learner. The question we investigate is whether it is possible to derive vanishing regret bounds that hold with…

Machine Learning · Computer Science 2026-02-19 Matthias Frey , Jonathan H. Manton , Jingge Zhu

Bounds for the expected return probability of the delayed random walk on finite clusters of an invariant percolation on transitive unimodular graphs are derived. They are particularly suited for the case of critical Bernoulli percolation…

Probability · Mathematics 2017-06-20 Florian Sobieczky

We study the problem of posterior sampling in the context of score based generative models. We have a trained score network for a prior $p(x)$, a measurement model $p(y|x)$, and are tasked with sampling from the posterior $p(x|y)$. Prior…

Machine Learning · Computer Science 2025-12-09 Advait Parulekar , Litu Rout , Karthikeyan Shanmugam , Sanjay Shakkottai

This paper is concerned with the formulation of $N$-mixture models for estimating the abundance and probability of detection of a species from binary response, count and time-to-detection data. A modelling framework, which encompasses…

Methodology · Statistics 2023-09-27 Linda M Haines , Res Altwegg , David L. Borchers

For many taxa, the current high rates of extinction are likely to result in a significant loss of biodiversity. The evolutionary heritage of biodiversity is frequently quantified by a measure called phylogenetic diversity (PD). We predict…

Populations and Evolution · Quantitative Biology 2013-06-13 Amaury Lambert , Mike Steel

One-dimensional disordered systems with a random potential of a small amplitude and short-range correlations are considered near the initial band edge. The evolution equation is obtained for the mutual ditribution P(\rho,\psi) of the…

Disordered Systems and Neural Networks · Physics 2023-10-24 I. M. Suslov

This article concerns second-order time discretization of subdiffusion equations with time-dependent diffusion coefficients. High-order differentiability and regularity estimates are established for subdiffusion equations with…

Numerical Analysis · Mathematics 2020-06-05 Bangti Jin , Buyang Li , Zhi Zhou

Evolution of gene regulation is crucial for our understanding of the phenotypic differences between species, populations and individuals. Sequence-specific binding of transcription factors to the regulatory regions on the DNA is a key…

Populations and Evolution · Quantitative Biology 2015-11-09 Murat Tuğrul , Tiago Paixão , Nicholas H. Barton , Gašper Tkačik
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