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Copy file name to clipboardexpand all lines: docs/awesome/awesome-agi-cocosci.md
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*[Infinite Latent Feature Models and the Indian Buffet Process](http://mlg.eng.cam.ac.uk/zoubin/papers/ibptr.pdf) - ***Gatsby Computational Neuroscience Unit Technical Report 2005-001***, 2005. [[All Versions](https://scholar.google.com/scholar?cluster=13180738480564152907&hl=en&as_sdt=0,5)].
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*[The Indian Buffet Process: An Introduction and Review](https://jmlr.org/papers/v12/griffiths11a.html) - ***Journal of Machine Learning Research***, 2011. [[All Versions](https://scholar.google.com/scholar?cluster=6301314251995890943&hl=en&as_sdt=0,5)]. Tom Griffiths and Zoubin Ghahramani's review on infinite models, including the Chinese Restaurant Process (CRP) and the Indian Buffet Process (IBP).
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*[The Indian Buffet Process: An Introduction and Review](https://jmlr.org/papers/v12/griffiths11a.html) - ***Journal of Machine Learning Research***, 2011. [[All Versions](https://scholar.google.com/scholar?cluster=6301314251995890943)]. The Indian buffet process is a stochastic process defining a probability distribution over equivalence classes of sparse binary matrices with a finite number of rows and an unbounded number of columns. This distribution is suitable for use as a prior in probabilistic models that represent objects using a potentially infinite array of features, or that involve bipartite graphs in which the size of at least one class of nodes is unknown. This work gives a detailed derivation of this distribution, and illustrate its use as a prior in an infinite latent feature model. The authors then review recent applications of the Indian buffet process in machine learning, discuss its extensions, and summarize its connections to other stochastic processes.
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*[Nonparametric Bayesian Logic](https://www.cs.ubc.ca/~nando/papers/npblog.pdf) - ***UAI'05***, 2005. [[All Versions](https://scholar.google.com/scholar?cluster=18267211625980322095&hl=en&as_sdt=0,5)]. The first paper integrating logic into non-parametric model.
Copy file name to clipboardexpand all lines: docs/awesome/awesome-angular.md
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*[angular-api-challenge](https://github.com/ppsdang/angular-api-challenge) - This repository hosts an Angular-based project designed as a api integration exercise.
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*[angular-exercises](https://github.com/kobi-hari-courses/angular-exercises) - Exercises on various Angular topics, including solutions and solution videos.
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*[angular-debug-quest](https://github.com/angular-courses-lab/angular-debug-quest) - Sharpen your skills at fixing bugs in Angular applications for a better understanding of the framework.
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##### Online Training
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*[fast-facts/ng-update](https://github.com/fast-facts/ng-update) - A Github Action that keeps your Angular CLI-based projects up-to-date via automated PRs based on `ng update`.
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*[npx-app-updater](https://github.com/DSI-HUG/ngx-app-updater) - When a new version of your application is deployed, this library will trigger a user notification to inform them that updates are available.
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*[ngx-update-app](https://github.com/Celtian/ngx-update-app) - Angular directive for updating app via service workers.
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*[Angular Caniuse](https://www.angular.courses/caniuse) - Track Angular features from preview to stable stages.
Copy file name to clipboardexpand all lines: docs/awesome/awesome-cl.md
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*[cl+j](https://common-lisp.net/project/cl-plus-j/) - A JNI-based interface to a JVM via CFFI. Not available on Quicklisp. Does not reliably work with all implementations. [Expat][14].
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See also:
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*[open-ldk](https://github.com/atgreen/openldk) - A Java JIT Compiler and Runtime in Common Lisp. [GPL3.0][89]. (Work In Progress)
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* "bridges the gap between Java and Common Lisp by incrementally translating Java bytecode into Lisp, which is then compiled into native machine code for execution. This unique approach allows Java classes to be seamlessly mapped to Common Lisp Object System (CLOS) classes, enabling effortless integration between Java and Common Lisp codebases."
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* "provides a practical solution for integrating Java libraries into a Lisp-based workflow without the need for an out-of-process Java runtime environment."
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## Objective-C ##
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*[objc-lisp-bridge](https://github.com/fiddlerwoaroof/objc-lisp-bridge) - A portable reader and bridge for interacting with Objective-C and Cocoa. [MIT][200].
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* for JSON libraries that don't do it natively (jzon, shasht and cl-json are able to *encode* CLOS objects to JSON out of the box, and cl-json has the ability to *decode* JSON objects into a "fluid-class" CLOS object.)
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*[cl-json-pointer](https://github.com/y2q-actionman/cl-json-pointer) - A JSON Pointer implementation. [MIT][200].
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*[cl-jwk](https://github.com/dnaeon/cl-jwk) - Common Lisp system for decoding public JSON Web Keys (JWK). BSD License.
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*[JOSE](https://github.com/fukamachi/jose) - A JSON Object Signing and Encryption (JOSE) implementation for Common Lisp. BSD_2Clause.
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and search for JSON RPC below.
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*[series](https://series.sourceforge.net/) - Functional style without any runtime penalty at all. [MIT][200].
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*[trivial-do](https://github.com/yitzchak/trivial-do/) - Additional dolist style macros for Common Lisp. [MIT][200].
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*[doplus](https://github.com/alessiostalla/doplus) – another extensible iteration library, similar to :for.
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*[cl-transducers](https://codeberg.org/fosskers/cl-transducers) - Ergonomic, efficient data processing. [LGPL3][9]. ([GitHub mirror](https://github.com/fosskers/cl-transducers))
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*[cl-transducers](https://github.com/fosskers/cl-transducers/) - Ergonomic, efficient data processing. [LGPL3][9].
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* "Transducers are an ergonomic and extremely memory-efficient way to process a data source. Here “data source” means simple collections like Lists or Vectors, but also potentially large files or generators of infinite data."
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* "It is, in general, the most complete implementation of the Transducer pattern."
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* a "modern" API with `map`, `filter`, `take`, `repeat`, `cycle`, `fold`…
Copy file name to clipboardexpand all lines: docs/awesome/awesome-godot.md
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-[Godot Google Play Game Services](https://github.com/Iakobs/godot-play-game-services) - Integrate Google Play Games Services in your Godot game.
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-[Godot Spin Button](https://github.com/yudinikita/godot-spin-button) - Horizontal Selector with extended options.
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-[Godot XR Tools](https://github.com/godotvr/godot-xr-tools) - Basic components for XR development.
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-[Health, HitBoxes, HurtBoxes, and HitScans](https://github.com/cluttered-code/godot-health-hitbox-hurtbox) - 2D and 3D Components to manage health, damage, and healing.
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-[HTerrain](https://github.com/Zylann/godot_heightmap_plugin) - Heightmap-based terrain. Supports texture painting, colouring, holes, level of detail and grass. *(Godot 3 and 4)*
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-[Icon Explorer](https://kenyoni-software.github.io/godot-addons/addons/icon_explorer) - Browse and save icons from popular icon collections.
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-[Importality](https://github.com/nklbdev/godot-4-importality) - raster graphics and animations importers: Aseprite, Krita, Pencil2D, Piskel, Pixelorama and others.
Copy file name to clipboardexpand all lines: docs/awesome/awesome-javascript.md
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*[Hegel](https://hegel.js.org/) - A static type checker for JavaScript with a bias on type inference an strong type system.
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*[TypL](https://github.com/getify/TypL) - the JavaScript Type Linter with a bias on type inference.
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*[Hindley Milner Definitions](https://github.com/xodio/hm-def) - runtime type checking for JavaScript functions using Haskell-alike Hindley Milner type signatures.
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*[Zod](https://github.com/colinhacks/zod) - TypeScript-first schema validation with built-in static type inference.
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## Testing Frameworks
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*[lunr](https://github.com/olivernn/lunr.js) - Library for use in the browser and It indexes JSON documents and provides a simple search interface for retrieving documents that best match text queries.
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*[flexsearch](https://github.com/nextapps-de/flexsearch) - It is a Next-Generation full text search library for Browser and Node.js.
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*[Elasticlunr](https://github.com/weixsong/elasticlunr.js) - This library is based on lunr.js, but more flexible and customized.
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## ORM
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*[Prisma](https://github.com/prisma/prisma) Next-generation ORM for Node.js & TypeScript | PostgreSQL, MySQL, MariaDB, SQL Server, SQLite, MongoDB and CockroachDB.
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*[Sequelize](https://github.com/sequelize/sequelize) Feature-rich ORM for modern Node.js and TypeScript | PostgreSQL, MySQL, MariaDB, SQLite, MS SQL Server, Snowflake, Oracle DB...
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*[Mongoose](https://github.com/Automattic/mongoose) MongoDB object modeling designed to work in an asynchronous environment.
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*[TypeORM](https://github.com/typeorm/typeorm) ORM for TypeScript and JavaScript, Works in NodeJS, Browser, Ionic, Cordova and Electron platforms.
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*[Drizzle ORM](https://github.com/drizzle-team/drizzle-orm) Headless TypeScript ORM with a head. Runs on Node, Bun and Deno.
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*[Kysely](https://github.com/kysely-org/kysely) A type-safe typescript SQL query builder.
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*[Knex](https://github.com/knex/knex) A query builder for PostgreSQL, MySQL, CockroachDB, SQL Server, SQLite3 and Oracle, designed to be flexible, portable, and fun to use.
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*[MikroORM](https://github.com/mikro-orm/mikro-orm) TypeScript ORM for Node.js based on Data Mapper, Unit of Work and Identity Map patterns.
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