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Found 10 papers, 7 papers with code
Computational Doob's h-transforms for Online Filtering of Discretely Observed Diffusions
This paper is concerned with online filtering of discretely observed nonlinear diffusion processes.
Simulating Diffusion Bridges with Score Matching
This is known to be a challenging problem that has received much attention in the last two decades.
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling
In contrast, solving the Schr\"odinger Bridge problem (SB), i. e. an entropy-regularized optimal transport problem on path spaces, yields diffusions which generate samples from the data distribution in finite time.
On Unbiased Estimation for Discretized Models
In this article, we consider computing expectations w. r. t.
Bayesian Inference
Computation
Numerical Analysis
Numerical Analysis
Methodology
Sequential Monte Carlo algorithms for agent-based models of disease transmission
Agent-based models of disease transmission involve stochastic rules that specify how a number of individuals would infect one another, recover or be removed from the population.
Computation Cellular Automata and Lattice Gases Populations and Evolution Methodology
Schrödinger Bridge Samplers
This is achieved by iteratively modifying the transition kernels of the reference Markov chain to obtain a process whose marginal distribution at time $T$ becomes closer to $\pi_T = \pi$, via regression-based approximations of the corresponding iterative proportional fitting recursion.
Multilevel Particle Filters for the Non-Linear Filtering Problem in Continuous Time
Under assumptions, this can achieve a mean square error of $\mathcal{O}(\epsilon^2)$, for $\epsilon>0$ arbitrary, such that the associated cost is $\mathcal{O}(\epsilon^{-4})$.
Numerical Analysis Numerical Analysis Probability
Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach
We propose a general statistical framework for clustering multiple time series that exhibit nonlinear dynamics into an a-priori-unknown number of sub-groups.
Unbiased Hamiltonian Monte Carlo with couplings
We propose a methodology to parallelize Hamiltonian Monte Carlo estimators.
Computation
Gibbs Flow for Approximate Transport with Applications to Bayesian Computation
Any measurable function $T:\mathbb{R}^{d}\rightarrow\mathbb{R}^{d}$ such that $Y=T(X)\sim\pi_{1}$ if $X\sim\pi_{0}$ is called a transport map from $\pi_{0}$ to $\pi_{1}$.
Computation
