Taliesin Beynon
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Mathematica
Projects
2016
Deep Learning for Mathematica
high-level, flexible, friendly deep learning
From 2016 to 2018, I led development of the neural network framework, which encompassed 50+ functions and objects. Since version 10.3 it has been part of the core Mathematica language. It covers a wide range of state-of-the-art deep learning functionality, in an interface that is extremely easy for scientists and engineers to use, rivaling and exceeding the ease-of-use of libraries like Keras. One notable use of the framework was to replace the filter-bank based gravitional wave detectors used …
2015
Cryptography for Mathematica
user-friendly cryptography API
Semantic Import for Mathematica
automated import and recognition of rich tabular data
Text Search for Mathematica
easy-to-use lucene-backed indexing engine
2014
Hierarchical Data in Mathematica
DataFrame-like construct for data science workflows
For Mathematica 11, I contributed the the new Dataset construct in Mathematica, which acts as a flexible container for tabular data. It involved a lot of interesting challenges around automated layout and deduction of types from unstructured data. The underlying technology scales to quite complicated nested use of Mathematica’s two native data structures, being lists $\{v_1,v_2,...\}$ and associations $\left<\left| k_1 \to v_1,k_2 \to v_2,... \right|\right>$. Because Mathematica is a …
2013
Facebook Data Analysis
analysis and visualization for popular blog by Stephen Wolfram
For this project, I helped Stephen Wolfram analyze a dataset of Facebook profiles we collected from volunteers who engaged with a previous project I worked on. We looked at the influence of the friendship paradox, correlations between various demographic variables, performed topic modeling on people’s facebook posts, and did cluster analysis on their friend graphs. The friendship paradox summarizes that, on average, your friends have more friends than you do, because popular people are …
2012
Wolfram|Alpha Facebook Analytics
free personal analytics for your Facebook profile
Wolfram|Alpha Pro
automatic analysis of user-uploaded datasets
2011
Sonifying Shakespeare
experiment in sonifying Shakespeare's plays
While instructing at the NKS summer school, I helped students from diverse backgrounds to implement their ideas in Mathematica. One of the my favorite projects was working with the artist Elizabeth Latta to visualize and computationally explore the famous Shakespeare play The Tempest. Among the many promising ideas we investigated, two in particular were interesting enough that I’d like to show them off. The beautiful drawings are Elizabeth’s work, and I planned and wrote the code. …
2010
Spatial Game Theory
package for experiments in evolutionary spatial game theory
SGT is a Mathematica package to unlock effortless explorations in evolutionary spatial game theory. Using SGT, you can setup, conduct and visualize experiments using a small number of functions and symbolic expressions to specify the initial distribution of agents, the topology of the grid, the strategies the agents employ, the payoff structure of the games they play, the rules used to update the agents and apply natural selection, whether and how mutation occurs, whether agents have access to …