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Stars
A Julia package for probability distributions and associated functions.
💨 A breath of fresh air for programming web apps in Julia
Positron, a next-generation data science IDE
Official implementation for "AutoTimes: Autoregressive Time Series Forecasters via Large Language Models"
blablado is an extensible Assistant that listens to your voice and can execute custom Python functions you provided. It can speak as well.
Foundation Models for Time Series
Set of tools to assess and improve LLM security.
✨✨Latest Advances on Multimodal Large Language Models
Core functions for the Julia (2nd) edition of the text Fundamentals of Numerical Computation, by Driscoll and Braun.
gpttools extends gptstudio for package development to help you document code, write tests, or even explain code
C++ Mathematical Expression Parsing And Evaluation Library https://www.partow.net/programming/exprtk/index.html
Meta-package for data analysis in Julia, modeled after the R tidyverse.
Combining tree-boosting with Gaussian process and mixed effects models
This is a library written in C++ for automatic identification of Unobserved Components models. It may be linked to many popular environments, at the moment R, Matlab and Octave. Contributors are wa…
Deep universal probabilistic programming with Python and PyTorch
Computing reachable states of dynamical systems in Julia
Functional tensors for probabilistic programming
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…
Regularization paths for regression models with grouped covariates
StateSpaceModels.jl is a Julia package for time-series analysis using state-space models.
High performance model preprocessing library on PyTorch
Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation
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 …
AtsPy: Automated Time Series Models in Python (by @firmai)
An unofficial Pytorch implementation of Attention based Multi-Modal New Product Sales Time-series Forecasting
The GitHub repository for the paper: “Time Series is a Special Sequence: Forecasting with Sample Convolution and Interaction“. (NeurIPS 2022)