{"arxiv_id":"2409.05757","incoming":{"papers":1,"sentences":1,"groups":[{"kind":"method_or_tool","label":"Uses its method or tool","papers":1,"sentences":1,"quotes":[{"arxiv_id":"2608.14938","title":"4U 1538-52 in a Heartbeat: Broadband X-ray Spectral Properties from XMM-Newton and NuSTAR","url":"/paper/2608.14938","section":"Observation and data reduction","sentence":"For the spectral analysis, we use [ref] , a Python library for X-ray spectral analysis with Bayesian inference via Markov Chain Monte Carlo (MCMC) sampling using the No U-Turn Sampler [ref] .","intent_p":1.0,"contests_p":null}]}],"unlabelled_sentences":0},"outgoing":{"papers":15,"sentences":18,"groups":[{"kind":"method_or_tool","label":"Uses the method or tool of","papers":5,"sentences":5,"quotes":[{"arxiv_id":"2101.09604","title":"UltraNest -- a robust, general purpose Bayesian inference engine","url":"/paper/2101.09604","section":"Comparison of inference time for various methods","sentence":"A popular implementation of NS used in X-ray spectral fitting can be found in [ref] , which interfaces the NS algorithm of [ref] with or .","intent_p":0.83,"contests_p":null},{"arxiv_id":"1402.0004","title":"X-ray spectral modelling of the AGN obscuring region in the CDFS: Bayesian model selection and catalogue","url":"/paper/1402.0004","section":"Comparison of inference time for various methods","sentence":"A popular implementation of NS used in X-ray spectral fitting can be found in [ref] , which interfaces the NS algorithm of [ref] with or .","intent_p":0.83,"contests_p":null},{"arxiv_id":"1912.11554","title":"Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro","url":"/paper/1912.11554","section":"Description of","sentence":"[ref] , a probabilistic programming library that implements the construction of hierarchical Bayesian models and the tools needed to perform the associated inference.","intent_p":0.95,"contests_p":null},{"arxiv_id":"1711.05101","title":"Decoupled Weight Decay Regularization","url":"/paper/1711.05101","section":"High-resolution spectroscopy with","sentence":"For this particular problem, we use the optimiser [ref] with default parameters and a learning rate of $5^-4$ for $10^5$ iterations.","intent_p":1.0,"contests_p":null},{"arxiv_id":"1412.6980","title":"Adam: A Method for Stochastic Optimization","url":"/paper/1412.6980","section":"High-resolution spectroscopy with","sentence":"This makes it possible to mobilise first-order optimisers [ref] using gradient information to find a satisfactory minimum for the problem.","intent_p":0.89,"contests_p":null}]},{"kind":"background","label":"Cites as background","papers":2,"sentences":2,"quotes":[{"arxiv_id":"astro-ph/0108426","title":"Sherpa: a Mission-Independent Data Analysis Application","url":"/paper/astro-ph/0108426","section":"Introduction","sentence":"Constraining the plausible values of these parameters given an X-ray spectrum is usually achieved using publicly available software, such as [ref] , [ref] , [ref] , or [ref] .","intent_p":0.87,"contests_p":null},{"arxiv_id":"1601.00670","title":"Variational Inference: A Review for Statisticians","url":"/paper/1601.00670","section":"High-resolution spectroscopy with","sentence":"For further insight, we direct the interested reader to the review by [ref] .","intent_p":0.99,"contests_p":null}]}],"unlabelled_sentences":11},"claims":[],"thresholds":{"intent_p":0.8,"supports_p":0.95,"contests_p":0.7},"method":"Citing sentences come from each paper's LaTeX source; every \\cite marks the sentence and the works it cites. Pith's classifier typed each sentence. A label is shown at intent probability 0.8 or more (0.95 for support), a contest at 0.7 or more. Measured accuracy against two blind model families is at https://pith.science/accuracy. The quoted sentences are the citing authors' own.","held_up":null,"_links":{"html":"https://pith.science/paper/2409.05757"}}