workspace for AA 228: decision making under uncertainty
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Updated
Jan 6, 2020 - Julia
workspace for AA 228: decision making under uncertainty
Shortest path routing for sailing craft
Chance-constrained control and pricing for natural gas networks using Julia/JuMP.
Unfortunately, FMUs (fmi-standard.org) are not differentiable by design. To enable their full potential inside Julia, FMISensitivity.jl makes FMUs fully differentiable, regarding to: states and derivatives | inputs, outputs and other observable variables | parameters | event indicators | explicit time | state change sensitivity by event
Rigorous moment propagation with partial information about moments and dependencies in Julia
Linear Regression with errors in both X and Y, correlated or not, confidence intervals and plots.
An open-source toolkit for entropic data analysis
Affine Invariant Markov Chain Monte Carlo (MCMC) Ensemble sampler
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