A Gaggia Classic control project using microcontrollers.

A Stanford Engineering Beamer Template, so that you don't have to make the template yourself.

Binary sequence set optimization for CDMA applications

Code generation with CVXPY

Stanford LaTeX poster template

Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlight).

Library for Model Based RL

Latex code for making neural networks diagrams

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

Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization

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

Compile your Julia Package

Fast, flexible and easy to use probabilistic modelling in Python.

Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

The Julia Programming Language

Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)

PyTorch deep learning projects made easy.

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

A set of kernel-based (Un)conditional independence tests including SDCIT (Lee and Honavar, UAI 2017)

Python code of Hilbert-Schmidt Independence Criterion

Bayesian Networks in Python

A memory-efficient implementation of DenseNets