Search Results for "numerical" - Page 2
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Showing 47 open source projects for "numerical"
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Transformers4Rec
Transformers4Rec is a flexible and efficient library
Transformers4Rec is an advanced recommendation system library that leverages Transformer models for sequential and session-based recommendations. The library works as a bridge between natural language processing (NLP) and recommender systems (RecSys) by integrating with one of the most popular NLP frameworks, Hugging Face Transformers (HF). Transformers4Rec makes state-of-the-art transformer architectures available for RecSys researchers and industry practitioners. Traditional recommendation... -
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DPM-Solver
Fast ODE Solver for Diffusion Probabilistic Model Sampling
...Diffusion models are powerful generative systems capable of producing high-quality images and other data, but traditional sampling methods often require hundreds or thousands of computational steps. The project introduces a specialized numerical solver designed to approximate the diffusion process using a small number of high-order integration steps. By reformulating the sampling problem as the solution of a diffusion-related ordinary differential equation, the solver can produce high-quality samples much more efficiently. This approach significantly reduces the computational cost required to generate images while maintaining strong generation quality. -
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The Algorithms - C #
Collection of various algorithms in mathematics, machine learning
...Within the C repository, contributors implement algorithms from many areas of computer science including sorting, searching, graph processing, mathematics, machine learning, and numerical methods. Each algorithm implementation is written to be readable and well documented so that students and developers can understand how the algorithm works internally. The repository is designed primarily as an educational resource that helps programmers study algorithm design and computational thinking. Contributors from around the world continually add new implementations and improvements, making the repository a collaborative learning project. -
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smclarify
Fairness aware machine learning. Bias detection and mitigation
...The label can have value(s) that designates that sample as having a "positive" outcome. A bias measure is a function that returns a bias metric. A bias metric is a numerical value indicating the level of bias detected as determined by a particular bias measure. A collection of bias metrics for a given dataset or a combination of a dataset and model. -
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Gym
Toolkit for developing and comparing reinforcement learning algorithms
...The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano. It makes no assumptions about the structure of your agent, and is compatible with any numerical computation library, such as TensorFlow or Theano. The gym library is a collection of test problems — environments — that you can use to work out your reinforcement learning algorithms. ... -
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A Synthetic Data Generator for producing mixed datasets described by relevant, irrelevant, and redundant features.
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Effective TensorFlow 2
TensorFlow tutorials and best practices
...The project focuses on helping developers write efficient, maintainable, and reliable TensorFlow code when building deep learning systems. It includes practical guidelines that explain common pitfalls in neural network training, such as numerical instability and gradient-related issues. The repository also demonstrates techniques for improving model performance, optimizing training loops, and debugging TensorFlow programs. Through examples and explanations, the project highlights how developers can structure machine learning code to improve readability and maintainability. ... -
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DeepLearning
Deep Learning (Flower Book) mathematical derivation
...It is edited by three world-renowned experts, Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Includes linear algebra, probability theory, information theory, numerical optimization, and related content in machine learning. At the same time, it also introduces deep learning techniques used by practitioners in the industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling and practical methods, and investigates topics such as natural language processing, Applications in speech recognition, computer vision, online recommender systems, bioinformatics, and video games. ... -
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Dive-into-DL-TensorFlow2.0
Dive into Deep Learning
This project changes the MXNet code implementation in the original book "Learning Deep Learning by Hand" to TensorFlow2 implementation. After consulting Mr. Li Mu by the tutor of archersama , the implementation of this project has been agreed by Mr. Li Mu. Original authors: Aston Zhang, Li Mu, Zachary C. Lipton, Alexander J. Smola and other community contributors. There are some differences between the Chinese and English versions of this book . This project mainly focuses on TensorFlow2... -
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TGAN
Generative adversarial training for generating synthetic tabular data
...The new model is simpler and gives better performance on many datasets. TGAN is a tabular data synthesizer. It can generate fully synthetic data from real data. Currently, TGAN can generate numerical columns and categorical columns. TGAN has been developed and runs on Python 3.5, 3.6 and 3.7. Also, although it is not strictly required, the usage of a virtualenv is highly recommended in order to avoid interfering with other software installed in the system where TGAN is run. For development, you can use make install-develop instead in order to install all the required dependencies for testing and code listing. ... -
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MatlabFunc
Matlab codes for feature learning
MatlabFunc is a collection of MATLAB functions developed by the ZJULearning group to support various tasks in computer vision, machine learning, and numerical computation. The repository brings together a wide range of utility scripts, algorithms, and implementations that serve as building blocks for research and development. These functions cover areas such as matrix operations, optimization, data processing, and visualization, making them broadly applicable across different research domains. ... -
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2D Statistical Models. Building: shape model, texture model and concatenated appearance model; Fitting: 1D profile ASM, 2D profile ASM, direct local texture constrained(LTC) ASM, basic AAM, ICIA AAM, IAIA AAM, etc.
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Computational Linear Algebra for Coders
Free online textbook of Jupyter notebooks
...Instead of emphasizing purely theoretical mathematics, the project takes a programming-oriented approach that helps developers understand how linear algebra algorithms are implemented in real computational systems. The course explores topics such as matrix decomposition, numerical stability, and optimization techniques that are essential for machine learning and data science applications. -
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Community Detection Modularity Suite
Suite of community detection algorithms based on Modularity
...The suite is based upon the fast community algorithm implemented by Aaron Clauset <aaron@cs.unm.edu>, Chris Moore, Mark Newman, and the R IGraph library Copyright (C) 2007 Gabor Csardi <csardi@rmki.kfki.hu>. It also makes of the classes available from Numerical Recipies 3rd Edition W. Press, S. Teukolsky, W. Vetterling, B. Flanne -
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Natural Language Analysis with Ngrams
NLP tool for statistical analysis of words, sentences, documents
...Furthermore, it is now just a NetBeans project without a final JAR. Furthermore, there will be a github version for anyone who wishes to contribute. In the future versions, user will be able to convert a single word to numerical data, to be able to compare two words and get the comparison data, and to be able to do the same for the sentences, paragraphs and documents. I will JAR-it once I decide that it can be called a final release. This project was made by creating a corpus from the Google Ngrams data for English Language, version 20120701. EOWL list of English words was used to filter-out the words from Ngrams data. ... -
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BONESA is an open source, user-friendly interface for tuning the numerical parameters of metaheuristics. This package includes a multi-objective parameter tuning algorithm and visualizations of the performance landscape.
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Gandalf is a computer vision and numerical algorithm library, written in C, which allows you to develop new applications that will be portable and run FAST. Dynamically reconfigurable vector, matrix and image structures allow efficient use of memory.
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Darwin 2: Java Framework for Evolutionary Computation (genetic algorithm, GA). A true framework with out-of-the-box functionality and extensibility of all classes. Interface-based pattern with dependency-injection to configure components.
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Developed as a final year project at Islamic University of Technology (IUT) during 2010 - 2011 academic year. This code is a simple implementation of real coded genetic algorithm for numerical optimization. Code is written in C/C++.
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Universal CNC (Computer Numerical Control) system with accompanying communication and graphics libraries
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Tools/libraries: analytical and numerical mathematical methods in ODE, PDE, Vector Calculus, Linear Algebra, Probability and Statistics, Numerical Methods, FEM, DSP. The current file release libham1.0 is for Geometric Integration of Hamiltonian Systems w
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Pattern recognition software package. It includes several classification and clustering algorithms. It can read data from a set of images, an ASCII file or a JDBC connection. A small TCP data server with its corresponding JDBC driver is included.
