AdalFlow: The library to build & auto-optimize LLM applications.

Qwen2.5 is the large language model series developed by Qwen team, Alibaba Cloud.

A comprehensive collection of KAN(Kolmogorov-Arnold Network)-related resources, including libraries, projects, tutorials, papers, and more, for researchers and developers in the Kolmogorov-Arnold N…

A toolkit with data-driven pipelines for physics-informed machine learning.

A PyTorch based deep-learning toolkit for developing DL models for physical systems

Repo of optimized training recipes for accelerating PyTorch workflows of AI driven surrogates for physical systems

Official respository for "Band-limited Coordinate Networks for Multiscale Scene Representation" | CVPR 2022

The standard package for data-centric AI and machine learning with label errors, finding mislabeled data, and uncertainty quantification. Works with most datasets and models.

A BERT model for scientific text.

Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for ano…

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Algorithms for outlier, adversarial and drift detection

A simple and flexible code for Reservoir Computing architectures like Echo State Networks

Repository for the Universal Differential Equations for Scientific Machine Learning paper, describing a computational basis for high performance SciML

PyTorch-FEniCS interface

Biologically-informed neural networks

Complement the article 'Differential Machine Learning' (Huge & Savine, 2020), including mathematical proofs and important implementation details for production

To enhance the nonlinearity of neural networks and increase their mapping abilities between the inputs and response variables, activation functions play a crucial role to model more complex relatio…

Statistics and Mathematics for Machine Learning, Deep Learning , Deep NLP

A differentiable PDE solving framework for machine learning

Code repository for the paper "Learning partial differential equations for biological transport models from noisy spatiotemporal data"

A Python implementation of global optimization with gaussian processes.

Lightweight Experiment & Resource Monitoring 📺

Approximating neural network loss landscapes in low-dimensional parameter subspaces for PyTorch

Must-read Papers on Physics-Informed Neural Networks.

functorch is JAX-like composable function transforms for PyTorch.

DiffNet: A FEM based neural PDE solver package

Scientific Machine Learning Tutorials