Homological exterior derivartive with integer coefficients
Incremental View Maintenance for TanStack DB based on Differential Dataflow
Terminal User Interface library with differential rendering for efficient text-based applications
Beta distribution differential entropy.
Gamma distribution differential entropy.
A point in polygon based on the paper Optimal Reliable Point-in-Polygon Test and Differential Coding Boolean Operations on Polygons
Normal distribution differential entropy.
Terminal User Interface library with differential rendering for efficient text-based applications
Inverse gamma distribution differential entropy.
Cauchy distribution differential entropy.
Cross platform differential updater for electron applications
D2TS is a TypeScript implementation of Differential Dataflow.
Lognormal distribution differential entropy.
Terminal User Interface library with differential rendering for efficient text-based applications
Terminal User Interface library with differential rendering for efficient text-based applications
Terminal User Interface library with differential rendering for efficient text-based applications
Transform a differential GTFS Realtime feed into a full dataset/dump.
A tool for generating differential updates for filter lists.
Arcsine distribution differential entropy.
Uniform distribution differential entropy.
Terminal User Interface library with differential rendering for efficient text-based applications
Exponential distribution differential entropy.
Terminal User Interface library with differential rendering for efficient text-based applications
Terminal User Interface library with differential rendering for efficient text-based applications
An incremental data-parallel dataflow platform
An incremental data-parallel dataflow platform
Proc macros for the arael optimization framework: #[arael::model], constraint codegen
Generic automatic differentiation for Rust
Nonlinear optimization framework with compile-time symbolic differentiation
Automatic differentiation using Bevy ECS as computation graph
surge synthesizer -- rungekutta filter
A Rust library for solving differential equations.
Differential graded algebras for agents — the algebraic structure underlying cohomology
Advanced join patterns in differential dataflow
Simple and powerful global optimization using a self-adapting differential evolution.
A high-performance automatic differentiation library for Rust
Differential is a numeric-based library will compare two datasets and give you three levels of comparison: report, group, and item level. Each level provides the sum of each dataset and the difference.
Differentiate development environment from production
Automate baremetal server actions with iPXE
differentiation.gem implement a kind of Automatic differentiation algorithm. It can convert Method/Proc to differentiable version.
Calculate the difference in time relative to now. Returns readable metrics (e.g. years_ago, days_ago, etc.)
Sabetsuka (差別化) makes it easy and painless to differentiate polynomials
A toolbox of numerical differential equation solvers written in pure Ruby. Currently there are multiple methods available to solve initial value ODEs (Dormand-Prince, Forward Euler, 2nd order Adams-Bashforth), boundary value ODEs (Linear Finite Element Galerkin), 2D Poisson's equation (5-point Laplacian), and the 1D advection equation (Upwind, Lax-Friedrichs, Leapfrog, Lax-Wendroff).
Implement Elastic Sensitivity mechanism which was invented by UBER
TealToad gives you all the tools required to create gradient based AI algorithms such as linear regression and neural networks.
numerical solution for ordinaray differential equations
This gem allows to do simulation runs of systems of ordinary differential equations of one independent variable using numerical Runge-Kutta methods for approximation. Contains some features like calculation of separate additive terms of the differential equations, calculation of custom expressions and logging and printing runs to csv files, which engineers may find convenient.
ignis-autograd adds a differentiable tensor (Ignis::Tensor) and a reverse-mode autograd tape on top of the Ignis GPU foundation. Build computation graphs over GPU arrays and get exact gradients (verified against finite differences). The building block for neural-network training in pure Ruby on an NVIDIA GPU.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.