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👋 Hi, my name is Dan Betea (@danbetea). I am a research and data scientist with degrees in mathematics (PhD) and computer science (BS). On this page I'll post small pieces of code that might be useful to the (statistical/machine learning/mathematical/physical/programming) community; languages included are Julia, Mathematica, Python, C/C++, and perhaps others.
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👀 My current interests, in order, are:
- machine/statistical learning;
- data science;
- adjacent subjects like simulations (e.g. Markov Chain Monte Carlo) and numerical methods therein;
- probability and statistics, mathematical physics, (algebraic) combinatorics.
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I am currently looking for new challenges in the industry. If you want to get in touch, see email below.
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💞️ I’m also always looking for collaborators on various aspects and projects from my interests listed above. Topics include:
- regression and classification models;
- transfer lerning (e.g. particular applications of neural style transfer to various fields);
- simulations and numerical aspects of various models in statistical mechanics and physics and adjancent fields;
- random sampling methods and Markov Chain Monte Carlo techniques.
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📫 How to reach me : firstName DOT lastName AT outlook DOT com.
Machine and statistical learning; AI; probability; numerical modeling and simulations; mathematical physics; combinatorics. Art on Instagram
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CNRS
- Paris
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06:33
(UTC +01:00) - https://www.instagram.com/danbetea/
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BetaEnsemblesSampling.jl
BetaEnsemblesSampling.jl PublicEigenvalue sampling from classical beta random matrix and log gas ensembles
Julia 1
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tracy_widom
tracy_widom PublicTracy--Widom GUE and GOE distributions in Mathematica using the Bornemann Fredholm method
Mathematica
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nst-experiments
nst-experiments PublicNeural style transfer experiments at human scale
Jupyter Notebook
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coupling-from-the-past
coupling-from-the-past PublicGenerates uniformly random alternating sign matrices using coupling from the past
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