Popular GitHub Repositories for Numerical Derivatives

Investment Research for Everyone, Everywhere.

Computer vision assisted tool to extract numerical data from plot images.

C++ DataFrame for statistical, Financial, and ML analysis -- in modern C++ using native types and contiguous memory storage

POT : Python Optimal Transport

Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)

A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods

Welcome to the Physics-based Deep Learning Book v0.3 - the GenAI Edition

A comprehensive library for machine learning and numerical computing. Apply Machine Learning with Rust leveraging first principles.

C++ openframeworks addon and examples integrating Google's TensorFlow numerical computation and machine learning library

(NeurIPS 2022) On Embeddings for Numerical Features in Tabular Deep Learning

PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks

Automatic Differentiation Library for Computational and Mathematical Engineering

Code for the paper "Learning Differential Equations that are Easy to Solve"

Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.

This repository is an implementation of Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis (SV2TTS) with a vocoder that works in real-time. SV2TTS is a three-stage deep learning framework that allows to create a numerical representation of a voice from a few seconds of audio, and to use it to condition a text-to-speech model trained to generalize to new voices.

Official Code for "Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory Prediction (CVPR 2024)"

Universal modeling and simulation of fluid mechanics upon machine learning. From the Boltzmann equation, heading towards multiscale and multiphysics flows.

A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations

Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)

Accelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation for every device that can run Swift - from watchOS to Linux