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Tensors and Dynamic neural networks in Python with strong GPU acceleration
Development repository for the Triton language and compiler
The fastest path to AI-powered full stack observability, even for lean teams.
Open source platform for the machine learning lifecycle
The GenAI Forecasting Agent · LLMs × Foundation Time Series Models
Combining tree-boosting with Gaussian process and mixed effects models
Scalable and user friendly neural 🧠 forecasting algorithms.
Foundation Models for Time Series
Computing reachable states of dynamical systems in Julia
Natural Gradient Boosting for Probabilistic Prediction
✨✨Latest Advances on Multimodal Large Language Models
Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristi…
Deep universal probabilistic programming with Python and PyTorch
gpttools extends gptstudio for package development to help you document code, write tests, or even explain code
Set of tools to assess and improve LLM security.
C++ Mathematical Expression Parsing And Evaluation Library https://www.partow.net/programming/exprtk/index.html
Probabilistic time series modeling in Python
This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a community of users and contributors by focusing initially o…
A Julia package for probability distributions and associated functions.
💨 A breath of fresh air for programming web apps in Julia
An intuitive library to extract features from time series.
Codebase for Time-series Generative Adversarial Networks (TimeGAN) - NeurIPS 2019
Forecast Reconciliation - Classical (bottom-up), optimal and heuristic combination forecast reconciliation procedures for cross-sectional, temporal, and cross-temporal linearly constrained time ser…
vineyard (v6d): an in-memory immutable data manager. (Project under CNCF, TAG-Storage)
The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter …
Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
Meta-package for data analysis in Julia, modeled after the R tidyverse.
StateSpaceModels.jl is a Julia package for time-series analysis using state-space models.