Langevin
PulseAugur coverage of Langevin — every cluster mentioning Langevin across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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New complexity bounds established for Moreau--Yosida Langevin sampling algorithm
Researchers have developed new complexity bounds for the Moreau--Yosida unadjusted Langevin algorithm (MYULA), a method used for sampling from probability distributions. The study focuses on distributions of the form $\…
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New Langevin-gradient method accelerates global optimization for non-convex functions
Researchers have developed a new approach to global optimization for smooth, non-convex functions, aiming to find the absolute minimum value with a specified probability. The proposed Langevin--gradient method separates…
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New theory quantifies convergence for Langevin-regularized SVGD
This paper introduces a new theoretical framework for understanding Langevin-regularized Stein Variational Gradient Descent (SVGD). The research establishes quantitative convergence guarantees to the target distribution…
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New theoretical bounds improve Langevin sampling for complex distributions
Researchers have developed new theoretical bounds for the Moreau--Yosida unadjusted Langevin algorithm (MYULA), a method used for sampling from complex probability distributions. The study focuses on nonsmooth composite…
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New research offers faster Markov chain convergence methods
Two new research papers propose novel methods for accelerating Markov chain convergence. The first paper introduces a criterion called asymptotic equivalence with the target, offering a direct route to convergence proof…
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New HMC algorithms tackle bias and accelerate sampling times · 7 sources tracked
Researchers have developed new methods to address bias and improve efficiency in Hamiltonian Monte Carlo (HMC) algorithms. One study extends the concept of bias delocalization to unadjusted HMC and underdamped Langevin …
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New Malliavin calculus method estimates counterfactual gradients for adaptive IRL
Researchers have developed a novel passive algorithm for adaptive inverse reinforcement learning (IRL) that reconstructs a forward learner's loss function by observing its gradients. This new method utilizes Malliavin c…