Pages that link to "Item:Q5743237"
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The following pages link to Theoretical Guarantees for Approximate Sampling from Smooth and Log-Concave Densities (Q5743237):
Displaying 50 items.
- New particle representations for ergodic McKean-Vlasov SDEs (Q4967864) (← links)
- (Q4969117) (← links)
- Variance Reduction for Dependent Sequences with Applications to Stochastic Gradient MCMC (Q4995114) (← links)
- (Q4998932) (← links)
- Maximum Entropy Methods for Texture Synthesis: Theory and Practice (Q4999346) (← links)
- Hausdorff dimension, heavy tails, and generalization in neural networks* (Q5020059) (← links)
- Limit behavior of the invariant measure for Langevin dynamics (Q5043621) (← links)
- A Proximal Markov Chain Monte Carlo Method for Bayesian Inference in Imaging Inverse Problems: When Langevin Meets Moreau (Q5044995) (← links)
- (Q5053256) (← links)
- (Q5053262) (← links)
- Global Convergence of Stochastic Gradient Hamiltonian Monte Carlo for Nonconvex Stochastic Optimization: Nonasymptotic Performance Bounds and Momentum-Based Acceleration (Q5058053) (← links)
- Markov Chain Importance Sampling—A Highly Efficient Estimator for MCMC (Q5066382) (← links)
- Bayesian Imaging Using Plug & Play Priors: When Langevin Meets Tweedie (Q5094615) (← links)
- On Irreversible Metropolis Sampling Related to Langevin Dynamics (Q5095483) (← links)
- A Random-Batch Monte Carlo Method for Many-Body Systems with Singular Kernels (Q5112563) (← links)
- Maximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach. Part II: Theoretical Analysis (Q5143323) (← links)
- (Q5148992) (← links)
- (Q5159403) (← links)
- (Q5159457) (← links)
- On Stochastic Gradient Langevin Dynamics with Dependent Data Streams: The Fully Nonconvex Case (Q5162623) (← links)
- (Q5214293) (← links)
- (Q5381127) (← links)
- Laplacian Smoothing Stochastic Gradient Markov Chain Monte Carlo (Q5856684) (← links)
- Stochastic Gradient Markov Chain Monte Carlo (Q5857155) (← links)
- Ensemble Kalman Sampler: Mean-field Limit and Convergence Analysis (Q5858114) (← links)
- Data-free likelihood-informed dimension reduction of Bayesian inverse problems (Q5859742) (← links)
- (Q5875524) (← links)
- ALMOND: Adaptive Latent Modeling and Optimization via Neural Networks and Langevin Diffusion (Q6040682) (← links)
- Birth–death dynamics for sampling: global convergence, approximations and their asymptotics (Q6050829) (← links)
- Global Optimization via Schrödinger–Föllmer Diffusion (Q6057791) (← links)
- Dimension Free Nonasymptotic Bounds on the Accuracy of High-Dimensional Laplace Approximation (Q6062239) (← links)
- Phase transitions for support recovery under local differential privacy (Q6062699) (← links)
- Convergence of Langevin-simulated annealing algorithms with multiplicative noise. II: Total variation (Q6073725) (← links)
- Unadjusted Langevin algorithm with multiplicative noise: total variation and Wasserstein bounds (Q6103981) (← links)
- Complexity results for MCMC derived from quantitative bounds (Q6104001) (← links)
- Laplace priors and spatial inhomogeneity in Bayesian inverse problems (Q6120819) (← links)
- Swarm gradient dynamics for global optimization: the mean-field limit case (Q6126662) (← links)
- (Non)-penalized multilevel methods for non-uniformly log-concave distributions (Q6126986) (← links)
- Distributed event-triggered unadjusted Langevin algorithm for Bayesian learning (Q6136164) (← links)
- The Langevin Monte Carlo algorithm in the non-smooth log-concave case (Q6138925) (← links)
- Unbiased Estimation Using Underdamped Langevin Dynamics (Q6141730) (← links)
- Taming Neural Networks with TUSLA: Nonconvex Learning via Adaptive Stochastic Gradient Langevin Algorithms (Q6162009) (← links)
- Multi-index antithetic stochastic gradient algorithm (Q6171790) (← links)
- The forward-backward envelope for sampling with the overdamped Langevin algorithm (Q6173566) (← links)
- Finite-sample complexity of sequential Monte Carlo estimators (Q6177328) (← links)
- Contraction and convergence rates for discretized kinetic Langevin dynamics (Q6552475) (← links)
- Hybrid unadjusted Langevin methods for high-dimensional latent variable models (Q6554220) (← links)
- NF-ULA: normalizing flow-based unadjusted Langevin algorithm for imaging inverse problems (Q6556790) (← links)
- Bayesian Robustness: A Nonasymptotic Viewpoint (Q6567906) (← links)
- Swing contract pricing: with and without neural networks (Q6581630) (← links)
