Newton's recursive mixture estimator is a discrete gradient flow on the Fisher-Rao manifold of probability measures.
Stochastic relaxation, gibbs distributions, and the bayesian restoration of images
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AI4BayesCode generates validated modular stateful MCMC samplers from natural language Bayesian model descriptions via LLM translation, modular blocks, and recursive stateful composition.
Parallel Picard-map algorithms for zeroth-order Random Walk Metropolis achieve O(sqrt(d)) parallel iterations with O(sqrt(d)) processors on log-concave distributions in d dimensions.
Hybrid Iterative-QAOA warm starts improve shipment delivery by up to 12% and cut drive distance by 6% on real logistics data when fed to a classical solver.
citing papers explorer
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Newton's Algorithm as a Gradient Flow: A Geometric Framework for Recursive Mixture Estimation
Newton's recursive mixture estimator is a discrete gradient flow on the Fisher-Rao manifold of probability measures.
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AI4BayesCode: From Natural Language Descriptions to Validated Modular Stateful Bayesian Samplers
AI4BayesCode generates validated modular stateful MCMC samplers from natural language Bayesian model descriptions via LLM translation, modular blocks, and recursive stateful composition.
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Parallel computations for Metropolis Markov chains with Picard maps
Parallel Picard-map algorithms for zeroth-order Random Walk Metropolis achieve O(sqrt(d)) parallel iterations with O(sqrt(d)) processors on log-concave distributions in d dimensions.
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Hybrid Quantum-Classical Optimization Workflows for the Shipment Selection Problem
Hybrid Iterative-QAOA warm starts improve shipment delivery by up to 12% and cut drive distance by 6% on real logistics data when fed to a classical solver.