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Let us document some key words for JuliaQuantum projects. Comment below if anything is missing or categorized badly or improper. Features have been implemented should also documented here. Details ca…
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私信
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Does scikit-learn currently include any structured-prediction methods (i.e. supervised learning for predicting vectors of variables).
Some examples would be graphical models (Markov Random Fields, H…
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ANovelProbabilityModelForBackgroundMaintenanceAndSubtraction.pdf
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Currently, the variance component parameters from different spatial models are not comparable.
See, for example, the globulus demo, which fits the same dataset using blocks, splines and an autoregress…
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Can tikz-bayesnet handle undirected graphs (no arrows on edges), like Markov Random Fields?
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To get myself familiar with OpenGM, I wrote an application where I build a simple 1-D Markov Random Field with 20 variables, smoothing factors between adjacent variables (SquaredDifferenceFunction) an…
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U de M
deep learnign and its applications (games, player match making)
1. intro to machien learning
2. deep learning paper
3. more recent aper for audo encoders
4. future work
Artifical definition …
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SymPy (http://sympy.org/en/index.html) is a Python library for symbolic mathematics.
My initial motivation for looking at SymPy resulted from #172 and #173. Instead of recoding all probability distri…
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The reason I want to mention directed acyclic graphs and Bayesian networks is for "SEO" or so we are discoverable on the web by people who refer to these things by these other names. Indeed, I see DA…