Simulation-Based Inference
PulseAugur coverage of Simulation-Based Inference — every cluster mentioning Simulation-Based Inference across labs, papers, and developer communities, ranked by signal.
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New AI method infers Hamiltonian parameters from RIXS spectroscopy data
Researchers have applied simulation-based inference, utilizing a vision transformer encoder, to analyze resonant inelastic X-ray scattering (RIXS) spectroscopy data. This novel approach efficiently restricts the prior a…
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New SBI-BOED method optimizes inference and experimental design
A new research paper introduces a method that bridges Simulation-Based Inference (SBI) and Bayesian Optimal Experimental Design (BOED). This approach, termed SBI-BOED, leverages mutual information bounds to simultaneous…
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LLM-assisted Bayesian agent accelerates mechanistic world model discovery
Researchers have developed a Model Discovery Agent (MDA) that uses large language models (LLMs) to assist in Bayesian experiment design for efficient discovery of mechanistic world models. MDA couples an LLM proposer wi…
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LLM-assisted agent designs experiments for efficient mechanistic world model discovery
Researchers have developed the Model Discovery Agent (MDA), an LLM-assisted system designed for efficient discovery of mechanistic world models through Bayesian experiment design. MDA couples a large language model for …
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New method uses neural networks to enhance Hamiltonian Monte Carlo for inference
Researchers have introduced Neural Surrogate HMC, a novel method that integrates neural likelihood estimation with Hamiltonian Monte Carlo for simulation-based inference. This approach leverages neural networks to appro…
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New papers introduce Simulation-Based Empirical Bayes for scientific inference
Two new papers introduce Simulation-Based Empirical Bayes (SBEB), a method for performing simultaneous inference across related latent variables when the likelihood is only available through a simulator. The first paper…
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New SBI Framework Tackles Systematic Uncertainties in High-Dimensional Data
Researchers have developed a new Simulation-Based Inference (SBI) framework designed to tackle the computational challenges of profiling systematic uncertainties in high-dimensional data analyses. This novel approach ut…
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Simulation-based inference offers faster Bayesian calibration for epidemiological models
A new research paper proposes simulation-based inference (SBI) as a faster and more efficient alternative to Markov chain Monte Carlo (MCMC) for calibrating epidemiological models. The study, which used COVID-19 ICU occ…
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Deep Neural Network Method Enhances Particle Physics Inference
A new paper on arXiv introduces a Simulation-Based Inference (SBI) method for estimating resonance parameters in particle physics, particularly for the rho(770) resonance. This deep neural network-driven approach demons…
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New research explores theoretical guidelines for Langevin dynamics in AI sampling
Researchers have published theoretical guidelines for annealed Langevin dynamics in compositional simulation-based inference, aiming to improve sampling accuracy by providing explicit decision rules for hyperparameters.…
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New method boosts neural likelihood surrogate training efficiency
Researchers have developed a new method to improve the efficiency of training neural likelihood surrogates for stochastic process models. By augmenting the standard loss function with exact score information and adaptiv…