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    <title>Pinboard (Vaguery)</title>
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    <description>recent bookmarks from Vaguery</description>
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    <title>[1411.1607] Julia: A Fresh Approach to Numerical Computing</title>
    <dc:date>2015-09-06T13:12:53+00:00</dc:date>
    <link>http://arxiv.org/abs/1411.1607</link>
    <dc:creator>Vaguery</dc:creator><description><![CDATA[Bridging cultures that have often been distant, Julia combines expertise from the diverse fields of computer science and computational science to create a new approach to numerical computing. Julia is designed to be easy and fast. Julia questions notions generally held as "laws of nature" by practitioners of numerical computing: 
1. High-level dynamic programs have to be slow. 
2. One must prototype in one language and then rewrite in another language for speed or deployment, and 
3. There are parts of a system for the programmer, and other parts best left untouched as they are built by the experts. 
We introduce the Julia programming language and its design --- a dance between specialization and abstraction. Specialization allows for custom treatment. Multiple dispatch, a technique from computer science, picks the right algorithm for the right circumstance. Abstraction, what good computation is really about, recognizes what remains the same after differences are stripped away. Abstractions in mathematics are captured as code through another technique from computer science, generic programming. 
Julia shows that one can have machine performance without sacrificing human convenience.
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<dc:subject>Julia-language programming computational-science Jupyter rather-interesting</dc:subject>
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    <title>[1109.2618] Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning</title>
    <dc:date>2012-01-05T13:34:06+00:00</dc:date>
    <link>http://arxiv.org/abs/1109.2618</link>
    <dc:creator>Vaguery</dc:creator><description><![CDATA[We introduce a machine learning model to predict atomization energies of a diverse set of organic molecules, based on nuclear charges and atomic positions only. The problem of solving the molecular Schr"odinger equation is mapped onto a non-linear statistical regression problem of reduced complexity. Regression models are trained on and compared to atomization energies computed with hybrid density-functional theory. Cross-validation over more than seven thousand small organic molecules yields a mean absolute error of ~10 kcal/mol. Applicability is demonstrated for the prediction of molecular atomization potential energy curves.
]]></description>
<dc:subject>machine-learning learning-from-data biochemistry computational-science nudge-targets</dc:subject>
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    <title>[1110.4876] REBOUND: An open-source multi-purpose N-body code for collisional dynamics</title>
    <dc:date>2012-01-01T14:35:58+00:00</dc:date>
    <link>http://arxiv.org/abs/1110.4876</link>
    <dc:creator>Vaguery</dc:creator><description><![CDATA[REBOUND is a new multi-purpose N-body code which is freely available under an open-source license. It was designed for collisional dynamics such as planetary rings but can also solve the classical N-body problem. It is highly modular and can be customized easily to work on a wide variety of different problems in astrophysics and beyond. 
]]></description>
<dc:subject>simulation computational-science astrophysics numerical-methods simulator library open-source nudge-targets</dc:subject>
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