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Probability Theory

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Probability Theory

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Research Frontiers in Markov Chain Monte Carlo Methods

Development of advanced sampling algorithms and convergence diagnostics for Bayesian inference and high-dimensional integration.

Spectral Gaps and Convergence Acceleration in High Dimensions
Adaptive Proposal Mechanisms for Pathological Posterior Geometries
Coupling Strategies in Non-Reversible Markov Dynamics
Multilevel MCMC and Computational Complexity Reduction
Implicit Bias of Gradient-Based Sampling Algorithms
Optimal Transport Metrics for Sampler Comparison
Scalable MCMC for Structured Latent Variable Models
Tempering and Mode Escape in Multimodal Inference
Variance Reduction Through Control Variates in Sampling
Information-Theoretic Limits of MCMC Estimation

All Probability Theory PhD categories