Search Results for "hidden markov model"
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Showing 142 open source projects for "hidden markov model"
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AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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statsmodels
Statsmodels, statistical modeling and econometrics in Python
...The package is released under the open source Modified BSD (3-clause) license. Generalized linear models with support for all of the one-parameter exponential family distributions. Markov switching models (MSAR), also known as Hidden Markov Models (HMM). Vector autoregressive models, VAR and structural VAR. Vector error correction model, VECM. Robust linear models with support for several M-estimators. statsmodels supports specifying models using R-style formulas and pandas DataFrames. -
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pomegranate
Fast, flexible and easy to use probabilistic modelling in Python
pomegranate is a library for probabilistic modeling defined by its modular implementation and treatment of all models as the probability distributions they are. The modular implementation allows one to easily drop normal distributions into a mixture model to create a Gaussian mixture model just as easily as dropping a gamma and a Poisson distribution into a mixture model to create a heterogeneous mixture. But that's not all! Because each model is treated as a probability distribution, Bayesian networks can be dropped into a mixture just as easily as a normal distribution, and hidden Markov models can be dropped into Bayes classifiers to make a classifier over sequences. ... -
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TensorFlow Probability
Probabilistic reasoning and statistical analysis in TensorFlow
...It's for data scientists, statisticians, ML researchers, and practitioners who want to encode domain knowledge to understand data and make predictions. Since TFP inherits the benefits of TensorFlow, you can build, fit, and deploy a model using a single language throughout the lifecycle of model exploration and production. TFP is open source and available on GitHub. Tools to build deep probabilistic models, including probabilistic layers and a `JointDistribution` abstraction. Variational inference and Markov chain Monte Carlo. A wide selection of probability distributions and bijectors. ... -
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Kaldi
kaldi-asr/kaldi is the official location of the Kaldi project
...It provides a powerful framework for building state-of-the-art automatic speech recognition (ASR) systems, with support for deep neural networks, Gaussian mixture models, hidden Markov models, and other advanced techniques. The toolkit is widely used in both academia and industry due to its flexibility, extensibility, and strong community support. Kaldi is designed for researchers who need a highly customizable environment to experiment with new algorithms, as well as for practitioners who want robust, production-ready ASR pipelines. ... -
Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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Bayesian Statistics
This repository holds slides and code for a full Bayesian statistics
This repository holds slides and code for a full Bayesian statistics graduate course. Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used... -
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Anti-Spam SMTP Proxy Server
Anti-Spam SMTP Proxy Server implements multiple spam filters
The Anti-Spam SMTP Proxy (ASSP) Server project aims to create an open source platform-independent SMTP Proxy server which implements auto-whitelists, self learning Hidden-Markov-Model and/or Bayesian, Greylisting, DNSBL, DNSWL, URIBL, SPF, SRS, Backscatter, Virus scanning, attachment blocking, Senderbase and multiple other filter methods. Click 'Files' to download the professional version 2.8.1 build 24261. A linux(ubuntu 20.04 LTS) and a freeBSD 12.2 based ready to run OVA of ASSP V2 are also available for download. ... -
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CL4R1T4S
Archive of leaked AI system prompts and internal instruction sets
CL4R1T4S is a public repository that collects and archives extracted system prompts, internal guidelines, and behavioral instructions used by various artificial intelligence models and agents. Its stated goal is to promote transparency by documenting the hidden prompt scaffolding that shapes how AI systems behave and respond to users. CL4R1T4S organizes these materials by company or product, with directories containing prompt files and related instructions for many well-known AI systems. These files typically include text documents that represent internal system messages, tool instructions, or operational guidelines that influence model responses. ... -
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Fastbot-Android Open Source Handbook
Testing tool for modeling GUI transitions
Fastbot_Android (Fastbot 2.0) is a model-based automated testing tool by ByteDance designed to discover stability or usability issues in Android apps by modeling GUI transitions rather than relying purely on random interactions. It blends machine learning and reinforcement-learning approaches to build a transition graph of UI states and use that model to intelligently explore possible user interactions — aiming to replicate more human-like usage patterns and uncover hidden bugs, crashes, or edge cases. ... -
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Octelium
A next-gen FOSS self-hosted unified zero trust secure access platform
Octelium is an open source, self-hosted unified secure-access platform built for modern infrastructure and hybrid environments. It positions itself as more than a typical VPN; it supports zero-trust network access (ZTNA), “BeyondCorp”-style access, API/AI gateway functionality, and even serves as a PaaS-like deployment surface. One of its key strengths is identity-based, application-layer (L7) aware control, meaning access decisions are made per request, with context and policy rather than... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Metarank
A low code Machine Learning service that personalizes articles
Metarank is a service that can personalize any type of content: product listings, articles, recommendations and search results in 3 easy steps with a few lines of code. It’s often considered "too risky" to spend 6+ months on an in-house moonshot project to reinvent the wheel without an experienced team and no existing open-source tools. Metarank makes it easy not only for Amazon to do personalization but for everyone else. Ingest historical item listings, clicks and item metadata so Metarank... -
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user.js
Firefox privacy, security and anti-tracking: a comprehensive user.js
...Everyone, experts included, should at least read the wiki, as it contains important information regarding a few user.js settings. Note that we do not recommend connecting over Tor on Firefox. Use the Tor Browser if your threat model calls for it, or for accessing hidden services. Also be aware that the arkenfox user.js is made specifically for desktop Firefox. Using it as-is in other Gecko-based browsers can be counterproductive, especially in the Tor Browser. -
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Attention Residuals (AttnRes)
Drop-in replacement for standard residual connections in Transformers
Attention Residuals is a research-driven architectural innovation for transformer-based models that replaces traditional residual connections with an attention-based mechanism to improve information flow across layers. In standard transformers, residual connections simply sum outputs from previous layers, which can lead to uncontrolled growth of hidden states and dilution of early-layer information in deep networks. Attention Residuals introduces a learnable softmax attention mechanism that... -
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files-to-prompt
Concatenate a directory full of files into a single prompt
files-to-prompt is a Python command-line tool that takes one or more files or entire directories and concatenates their contents into a single, LLM-friendly prompt. It walks the directory tree, outputting each file preceded by its relative path and a separator, so a model can understand which content came from where. The tool is aimed at workflows where you want to ask an LLM questions about a whole codebase, documentation set, or notes folder without manually copying files together. It includes rich filtering controls, letting you limit by extension, include or skip hidden files, and ignore paths that match glob patterns or .gitignore rules. ... -
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Gen.jl
A general-purpose probabilistic programming system
...Gen’s inference library gives users building blocks for writing efficient probabilistic inference algorithms that are tailored to their models, while automating the tricky math and the low-level implementation details. Gen helps users write hybrid algorithms that combine neural networks, variational inference, sequential Monte Carlo samplers, and Markov chain Monte Carlo. Gen features an easy-to-use modeling language for writing down generative models, inference models, variational families, and proposal distributions using ordinary code. But it also lets users migrate parts of their model or inference algorithm to specialized modeling languages for which it can generate especially fast code. ... -
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OpenAI DALL·E AsyncImage SwiftUI
OpenAI swift async text to image for SwiftUI app using OpenAI
...They are Markov chains trained using variational inference. The goal of diffusion models is to learn the latent structure of a dataset by modeling the way in which data points diffuse through the latent space. -
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Qooxdoo JavaScript Framework
qooxdoo - Universal JavaScript Framework
qooxdoo is a universal JavaScript framework that enables you to create applications for a wide range of platforms. With its object-oriented programming model, you build rich, interactive applications (RIAs), native-like apps for mobile devices, light-weight traditional web applications or even applications to run outside the browser. You leverage its integrated tool chain to develop and deploy applications of any scale while taking advantage of modern web technologies like HTML5 and CSS3,... -
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Tomb
the Crypto Undertaker
...Tomb’s model suits people who want encrypted containers with Unix-friendly ergonomics, keeping secrets safe while integrating cleanly into everyday scripts and workflows. -
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XD1DD
XD1DD: X-ray Diffraction for 1 Dimensional Disorder
The computer program is designed to calculate powder X-ray diffraction patterns for one-dimensionally (1D) disordered crystals, i.e. containing planar defects. Calculations are made on the basis of statistical models, where the Markov chain with stationary transition probabilities is used as a probabilistic rule for generating a 1D disordered sequence of layers. The model takes into account the short-range order in the alternation and methods of layer superposition, which allows simulating various cases of distribution of planar defects in crystals. To obtain a powder diffraction pattern, calculations are carried out in three-dimensional reciprocal space along rods passing through the nodes of the reciprocal two-dimensional lattice. ... -
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SCID Recast
The SCID 5 format in a clean, deterministic, modular architecture
SCID Recast is a deterministic, modern architecture modernizing the core database and indexing subsystem from first principles. It preserves compatibility with existing si5 databases while restructuring the core into a clean, modular C library (libscidcore) with well‑defined boundaries for database, game model, search, engine integration, and metadata. The project emphasizes reproducibility, explicit invariants, a clear error model, and a stable foundation for supporting archival workflows... -
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Whisper-Transcriber-Tool
Desktop application that converts video files into accurate text
WhisperTranscriber is a free, powerful desktop application that converts video files into accurate text using OpenAI's Whisper AI model. Perfect for journalists, researchers, students, content creators, and anyone who needs reliable transcription. KEY FEATURES: - High-accuracy AI transcription with 99+ language support - Works completely offline - no internet required, total privacy - Supports all common video formats (mp4) - Batch processing for multiple files - Automatic language detection - Drag & drop interface - Export as SRT formats - No file size limits PORTABLE VERSION: - No installation needed - Run from USB or any folder - FFmpeg and AI models included - Lightweight and fast WHY CHOOSE WHISPERTRANSCRIBER: ✓ 100% free forever - no subscriptions or hidden costs ✓ Complete privacy - all processing happens on your computer ✓ No account or registration required ✓ Professional-grade accuracy ✓ Works offline -
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CAMPARI
Software for molecular simulations and trajectory analysis
We are proud to introduce version 5 of CAMPARI. We have added a number of new features, most notably a Python interface for interpreting user-supplied code (with the help of ForPy), a novel trajectory storage standard (with the help of libpqxx/PostgreSQL), and a module for performing transition path theory. Naturally, CAMPARI continues to provide the reference implementation of the ABSINTH force field paradigm and implicit solvation model. CAMPARI is a joint package for performing and... -
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GalaxyBudsClient
Unofficial Galaxy Buds Manager for Windows, macOS, Linux, and Android
GalaxyBudsClient is a cross-platform desktop app to configure and control any Samsung Galaxy Buds model. It offers all standard features from the official Android app and goes beyond: fine-tune audio, customize touch gestures, monitor battery and firmware, integrate with your system, and unlock extra functions not available in stock software. With it, you can fully unleash the potential of your earbuds, tailor them to your personal workflow, and manage them seamlessly without needing a... -
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MLP Network Configurator
interactive tool designed to help users understand how neural network
...It provides real-time training feedback, intuitive architecture visualization, and even camera-based dataset collection — ideal for students, teachers, hobbyists, and curious minds. 💡 Key Features - Data Handling: Load, normalize, and validate datasets (JSON format). - Model Configuration: Define hidden layers, activation functions, loss and optimizer types. - Training: Visualize loss curves, predictions, PCA-based class separation. - Testing: Accuracy calculation, error graphs, confusion matrix, misclassified sample montage. - Camera Dataset Builder: Capture and label images live via webcam. - Model Insight: Animated weight & bias evolution, interactive heatmaps... -
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ava
AVA - Adversarial Variational Autoencoders
Both VAE and GAN have their own strong points although they share and imply underline theory of statistics as well as incredible complex via hidden layers of DNN when DNN becomes effective encoding/decoding functions without concrete specifications. This research unifies VAE and GAN into a consistent and consolidated model called Adversarial Variational Autoencoders (AVA) in which VAE and GAN complement each other, for instance, VAE is a good data generator by encoding data via excellent ideology of Kullback-Leibler divergence and GAN is a significantly important method to assess reliability of data which is realistic or fake. ... -
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UnBBayes
Framework & GUI for Bayes Nets and other probabilistic models.
UnBBayes is a probabilistic network framework written in Java. It has both a GUI and an API with inference, sampling, learning and evaluation. It supports Bayesian networks, influence diagrams, MSBN, OOBN, HBN, MEBN/PR-OWL, PRM, structure, parameter and incremental learning. Please, visit our wiki (https://sourceforge.net/p/unbbayes/wiki/Home/) for more information. Check out the license section (https://sourceforge.net/p/unbbayes/wiki/License/) for our licensing policy.
