65c05

Documents about 65c05

• Bounded independence for the inverse star discrepancy#616496arXiv (OAI Expanded)
• Bounded independence for the inverse star discrepancy#616996arXiv (All)
• On theoretical guarantees and a blessing of dimensionality for nonconvex sampling#633207arXiv (OAI Expanded)
• On theoretical guarantees and a blessing of dimensionality for nonconvex sampling#635556arXiv (All)
• Hypocoercivity of Tempered Bouncy Particle Samplers for Heavy-Tailed Targets#796881arXiv (OAI Expanded)
• Hypocoercivity of Tempered Bouncy Particle Samplers for Heavy-Tailed Targets#798294arXiv (All)
• Mean Square Error Analysis of Stochastic Runge-Kutta Integrators#1012345arXiv (All)
• Optimal Stopping with Randomly Arriving Stopping Opportunities#789364arXiv (OAI Expanded)
• Optimal Stopping with Randomly Arriving Stopping Opportunities#793368arXiv (All)
• Mode Coverage in Normalizing Flow Boltzmann Generators via Log-Ratio Variation#987215arXiv (All)
• Asymptotically optimal bracketing covers for anchored boxes with applications to star discrepancy#998316arXiv (All)
• Analysis of multilevel Monte Carlo path simulation using the Milstein discretisation#927067arXiv (All)
• Accelerated Sampling with the Inertial Langevin Algorithm#972393arXiv (All)
• Posterior Convergence without Force Convergence: Resolution-Stable Sampling for Rough Bayesian Inverse Problems#998336arXiv (All)
• Algebraic Structure of Vector Fields in Financial Diffusion Models and its Applications#141582arXiv (OAI)
• An Euler scheme for BSDEs via the Wiener chaos decomposition#971737arXiv (All)
• Post-Corrected Raw-Score Martingale Posterior Sampling for von Mises-Fisher Models#972047arXiv (All)
• Exploiting Exact Conditionals Improves Conditioning: Provably Fast Mixing Time Bounds By Sampling from the Marginal#779791arXiv (OAI Expanded)
• Exploiting Exact Conditionals Improves Conditioning: Provably Fast Mixing Time Bounds By Sampling from the Marginal#781166arXiv (All)
• A discontinuous Galerkin approximation of the Dean--Kawasaki equation#974782arXiv (All)
• Adjoint DSMC Method for Spatially Inhomogeneous Boltzmann Equation with General Boundary Conditions#821815arXiv (All)
• Geometric Ergodicity of Affine Invariant Ensemble Langevin and its Discrete Time Variants#925669arXiv (All)
• Fast Mixing of Data Augmentation Algorithms: Bayesian Probit, Logit, and Lasso Regression#158651arXiv (OAI)
• Extended Walk-on-Spheres Algorithm for Linear and Nonlinear Elliptic Problems of Divergence-type#623270arXiv (OAI Expanded)
• Extended Walk-on-Spheres Algorithm for Linear and Nonlinear Elliptic Problems of Divergence-type#625543arXiv (All)
• Windowed thinning and query complexity for the bouncy particle and Zigzag samplers#821966arXiv (All)
• Computing statistical Euler limits of the Navier--Stokes equations in three dimensions#985227arXiv (All)
• Estimating the asymptotics of integer partitions in intermediate dimensions ($d = 3,4,5,6$)#921167arXiv (OAI Expanded)
• Estimating the asymptotics of integer partitions in intermediate dimensions ($d = 3,4,5,6$)#925403arXiv (All)
• The Gaussian Latent Machine: Efficient Prior and Posterior Sampling for Inverse Problems#144295arXiv (OAI)
• Residual neural networks overcome the curse of dimensionality for semilinear heat equations#926528arXiv (All)
• A Noise-Aware Quantum Algorithm for Credit Valuation Adjustments on Real Quantum Hardware#984194arXiv (All)
• Signed random Fourier features for fast density estimation with indefinite kernels#790055arXiv (OAI Expanded)
• Signed random Fourier features for fast density estimation with indefinite kernels#794074arXiv (All)
• Deep neural networks with ReLU, leaky ReLU, and softplus activation provably overcome the curse of dimensionality for Kolmogorov partial differential equations with Lipschitz nonlinearities in the $L^p$-sense#179046arXiv (OAI)
• Deep neural networks with ReLU, leaky ReLU, and softplus activation provably overcome the curse of dimensionality for Kolmogorov partial differential equations with Lipschitz nonlinearities in the $L^p$-sense#179244arXiv (OAI Expanded)
• Deep neural networks with ReLU, leaky ReLU, and softplus activation provably overcome the curse of dimensionality for Kolmogorov partial differential equations with Lipschitz nonlinearities in the $L^p$-sense#179639arXiv
• Deep neural networks with ReLU, leaky ReLU, and softplus activation provably overcome the curse of dimensionality for Kolmogorov partial differential equations with Lipschitz nonlinearities in the $L^p$-sense#180501arXiv Biology