Hamiltonian Monte Carlo
PulseAugur coverage of Hamiltonian Monte Carlo — every cluster mentioning Hamiltonian Monte Carlo across labs, papers, and developer communities, ranked by signal.
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Diffusion models accelerate Schwinger model sampling in physics research
Researchers have explored a novel diffusion-based method for accelerating the sampling of the Schwinger model, a problem in lattice quantum field theory. They developed a U(1)-equivariant score-based generative model to…
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AI models enhance cosmological inference and uncertainty analysis
Two new arXiv papers explore the application of neural networks in cosmology. The first paper introduces a neural marking scheme to extract more cosmological information than traditional methods, significantly tightenin…
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AI diffusion models successfully sample SU(N) lattice gauge theories
Researchers have developed a diffusion model capable of sampling SU(N) lattice gauge theories, a significant advancement for computational physics. This implicit score matching framework was successfully applied to SU(3…
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New TSMC method optimizes trajectories and policies with differentiable dynamics
Researchers have introduced Tempered Sequential Monte Carlo (TSMC), a novel sampling-based framework for optimizing trajectories and policies within systems that have differentiable dynamics. This approach reframes cont…