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8 search results found

Course Content ⭐ 2,527

NMA Computational Neuroscience course

Graph Theory ⭐ 178

Julia and Python complex system applications in ecology, epidemiology, sociology, economics & finance; network science models including Bianconi-Barabási, Barabási-Albert, Watts-Strogatz, Waxman Model & Erdős-Rényi; graph theory algorithms involving Gillespie, Bron Kerbosch, Ramsey, Bellman Ford, A*, Kruskal, Borůvka, Prim, Dijkstra, DSatur, Randomized Distributed, Vizing, Topological Sort, DFS, BFS

Kalman Filter ⭐ 127

Kalman Filter implementation in Python using Numpy only in 30 lines.

Control Notes ⭐ 12

Notes on topics ranging from Recurrent Newtorks to Automatic Control and Reinforcement Learning

Sim.diffproc ⭐ 7

An R package for symbolic and numerical computations on scalar and multivariate systems of stochastic differential equations (SDEs). It provides users with a wide range of tools to simulate, estimate, analyze, and visualize the dynamics of these systems in both forms Itô and Stratonovich <doi:10.18637/jss.v096.i02>.

Neural Ode ⭐ 7

Phase Space ⭐ 6

Realtime 3-dimensional phase portraits in phase space

Spring Interpolator ⭐ 6

An Animation-Interpolator, "reverse-engineered" from facebook/rebound

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