Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…

Kolmogorov Arnold Networks

A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API

Flax is a neural network library for JAX that is designed for flexibility.

Probabilistic reasoning and statistical analysis in TensorFlow

Fast and Easy Infinite Neural Networks in Python

Puzzles for learning Triton

All the handwritten notes 📝 and source code files 🖥️ used in my YouTube Videos on Machine Learning & Simulation (https://www.youtube.com/channel/UCh0P7KwJhuQ4vrzc3IRuw4Q)

Computational Fluid Dynamics in JAX

Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations

18.335 - Introduction to Numerical Methods course

A 15TB Collection of Physics Simulation Datasets

CLU lets you write beautiful training loops in JAX.

Large-Scale Multimodal Dataset of Astronomical Data

Class materials for computational physics course

Posterior Sampling using Latent Diffusion

scores: Metrics for the verification, evaluation and optimisation of forecasts, predictions or models.

Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation

Stochastic Normalizing Flows

Spectral Neural Operator

A Pytorch Implementation of Attentive Neural Process

Mixture Density Networks (Bishop, 1994) tutorial in JAX

JAX-SPH: A Differentiable Smoothed Particle Hydrodynamics Framework

Spectral Methods in Python

Scientific Machine Learning Tutorials

Codes for Numerical Analysis course

an Open Collaborative project to explore the implications — theoretical or practical — of the PDE perspective of ConvNets

Efficient Differentiable n-d PDE solvers in JAX.

Fractional White Noises for Neural Stochastic Differential Equations (NeurIPS 2022)