Search Results for "simulation model library" - Page 28
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Showing 2367 open source projects for "simulation model library"
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CoolplaySpark
Spark Cool Play: Spark source code analysis, Spark class library, etc.
CoolplaySpark is a learning and practice repository designed to help users understand and work with Apache Spark. It serves as a companion resource for the book 深入理解Spark核心思想与源码分析 (In-Depth Understanding of Spark’s Core Concepts and Source Code Analysis). The project contains annotated examples, explanations, and exercises that guide learners through Spark’s architecture, execution model, and source code internals. It is particularly valuable for developers who want to strengthen their... -
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Deep learning time series forecasting
Deep learning PyTorch library for time series forecasting
Example image Flow Forecast (FF) is an open-source deep learning for time series forecasting framework. It provides all the latest state-of-the-art models (transformers, attention models, GRUs) and cutting-edge concepts with easy-to-understand interpretability metrics, cloud provider integration, and model serving capabilities. Flow Forecast was the first time series framework to feature support for transformer-based models and remains the only true end-to-end deep learning for time series... -
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Faster-Rcnn
This is a pytorch implementation library of faster-rcnn
Faster-Rcnn is a PyTorch implementation of the Faster R-CNN two-stage object detection model. It is designed for training and evaluating detectors on VOC-format datasets, including VOC07+12 and custom datasets arranged with VOC-style annotations and images. The repository includes scripts for training, prediction, evaluation, annotation generation, and model summary inspection. It supports backbone options through pretrained VGG and ResNet weights, making it useful for comparing feature... -
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Provider
InheritedWidgets, but simple
...Many apps use provider as a baseline pattern, and later evolve toward more advanced solutions as complexity grows—without discarding the conceptual model provider introduces. -
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Harmonica
A simple, physics-based animation library
Harmonica is a Go animation library based on simple physics simulation. It provides tools for creating smooth, natural motion in 2D and 3D applications. The project includes spring animation behavior that can make interface movement feel more organic than fixed linear transitions. It also includes projectile-style simulation that is useful for particles, motion effects, and game-like interactions. -
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SwagGen
OpenAPI/Swagger 3.0 Parser and Swift code generator
...SwagGen includes a bundled template for generating a client-side Swift library for interfacing with the Swagger spec. It includes support for model inheritance, shared enums, discrete and mutable request objects, inline schemas, Codable and Equatable models, configurable options, generic networking stack, and many other niceties. -
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Catalyst
Accelerated deep learning R&D
Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make... -
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TPLS
High Resolution Direct Numerical Simulation (DNS) of Two-Phase Flows
...Domains with up to 300,000,000 cells have been simulated. We also provide a simplified version of the code 'S-TPLS' to help new users understand the code structure and algorithms. The next step will be to include a model of boiling. -
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AugLy
A data augmentations library for audio, image, text, and video
...AugLy is a great library to utilize for augmenting your data in model training, or to evaluate the robustness gaps of your model! We designed AugLy to include many specific data augmentations that users perform in real life on internet platforms like Facebook's -- for example making an image into a meme, overlaying text/emojis on images/videos, reposting a screenshot from social media. -
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m2cgen
Transform ML models into a native code
m2cgen (Model 2 Code Generator) - is a lightweight library that provides an easy way to transpile trained statistical models into a native code (Python, C, Java, Go, JavaScript, Visual Basic, C#, PowerShell, R, PHP, Dart, Haskell, Ruby, F#, Rust, Elixir). Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies. -
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bert4keras
Keras implement of transformers for humans
Our light reimplementation of bert for keras. A cleaner, lighter version of bert for keras. This is the keras version of the transformer model library re-implemented by the author and is committed to combining transformer and keras with as clean code as possible. The original intention of this project is for the convenience of modification and customization, so it may be updated frequently. Load the pre-trained weights of bert/roberta/albert for fine-tune. Implement the attention mask required by the language model and seq2seq. ... -
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QBlade
Wind Turbine Rotor Design and Simulation
QBlade 2.0 released!!!! QBlade 2.0 released!!!! QBlade 2.0 released!!!! This project page is discontinued, you find our new webpage at: https://qblade.org/ This project page wont be updated in the future, however, everything in the "Files" section and the Forum Content will remain avaliable to everyone... -
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Texar-PyTorch
Integrating the Best of TF into PyTorch, for Machine Learning
...Texar-PyTorch integrates many of the best features of TensorFlow into PyTorch, delivering highly usable and customizable modules superior to PyTorch native ones. Texar-PyTorch (this repo) and Texar-TF have mostly the same interfaces. Both further combine the best design of TF and PyTorch. Data processing, model architectures, loss functions, training and inference algorithms, evaluation, etc. -
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RQ-Transformer
Implementation of RQ Transformer, autoregressive image generation
...For autoregressive (AR) modeling of high-resolution images, vector quantization (VQ) represents an image as a sequence of discrete codes. A short sequence length is important for an AR model to reduce its computational costs to consider long-range interactions of codes. However, we postulate that previous VQ cannot shorten the code sequence and generate high-fidelity images together in terms of the rate-distortion trade-off. -
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Unified Code Generation
Open-source code generator for Simulink/Stateflow
...Some of the strengths of UCGN: - Clearly readable source-code - Separation of functionality and parameters ("tunable parameters") - Robust data storage (compile-time static structures in favor of pointer run-time constructs) - Clear software architecture, direct correspondence to the model architecture - Separation of reusable library code - Simplicity and uniformity of software interfaces (for testing etc.) The following features are supported by the Simulink/UCGN - Discrete single-rate Simulink models and libraries - Block library with 50+ standard Simulink blocks - Periodic, condition-driven Stateflow charts (including flowgraphs, loops) - Structured data types through bus objects - Simulink native enumer -
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LSA runs based on C++ for Gibbs samplers and R / Rcpp for data preprocessing and posterior sample analysis. The Tempest depends on the Stan math library. We should build the Stan math library, and then you can build the executable.
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NetworkResponse Retrofit adapter
Retrofit call adapter to model success/failed responses as sealed type
This library provides a Kotlin Coroutines-based Retrofit call adapter for wrapping your API responses in a NetworkResponse sealed type. -
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GroIMP
Growth-grammar related Interactive Modelling Platform
Important: Groimp migrates to Gitlab. You can find the latest code at "https://gitlab.com/grogra/groimp/". The version on Sourceforge will not be updated anymore. The modelling platform GroIMP is designed as an integrated platform which incorporates modelling, visualisation and interaction. It exhibits several features which makes itself suitable for the field of biological or ALife modelling: The “modelling backbone” consists in the language XL. It is fully integrated, e.g., the... -
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ViennaSHE is a modern semiconductor device simulator for 1D, 2D and 3D device simulation. It relies on deterministic solutions of the Boltzmann Transport Equation using Spherical Harmonics Expansions.
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Major looseless compression algorithms library and documentation. First project: Arithmetic, Huffman, LZ77, LZ78, LZW, RLE. Second project reimplements Deflate. Documentation explains major Entropy Compression Methods.
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mometa
R&D-oriented low-code meta-programming, code visual editing, etc.
Mometa is not a traditional mainstream low-code platform (such as amis/Yunfengdie), mometa is a research and development-oriented, code visual design and editing platform; it is more like Dreamweaver, gui visual editing for programmers. The positioning of mometa is more based on the local development mode of programmers, adding the ability of visual coding (modification is also the local code file itself); it is more like an auxiliary coding tool, rather than No-Code (amis/Cloud Phoenix... -
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Differ
Swift library to generate differences and patches between collections
...There’s a lot more to calculating diffs than performing table view animations easily. Wherever you have code that propagates added/removed/moved callbacks from your model to your user interface, you should consider using a library that can calculate differences. Animating small batches of changes is usually going to be faster and provide a more responsive experience than reloading all of your data. Calculating and acting on differences should also aid you in making a clear separation between data and user interface, and hopefully provide a more declarative approach: your model performs state transition, then your UI code performs appropriate actions based on the calculated differences to that state. -
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Kotpref
Android SharedPreferences delegation library for Kotlin
Android SharedPreferences delegation library for Kotlin. -
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Mesh2HRTF is an open-source project aiming at providing an easy-to-use software package for the numerical calculation of HRTFs. It targets researchers in the field of binaural audio. In a nutshell, Mesh2HRTF simply reads geometrical data, calculates the corresponding sound field and outputs HRTFs. To support multiple computer platforms, the concept of Mesh2HRTF is to focus on a command-line tool, which forms the numerical core, i.e., an implementation of the 3-dimensional Burton-Miller...
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MACE
Deep learning inference framework optimized for mobile platforms
...Chip-dependent power options like big.LITTLE scheduling, Adreno GPU hints are included as advanced APIs. UI responsiveness guarantee is sometimes obligatory when running a model. Mechanism like automatically breaking OpenCL kernel into small units is introduced to allow better preemption for the UI rendering task. Graph level memory allocation optimization and buffer reuse are supported. The core library tries to keep minimum external dependencies to keep the library footprint small.
