mekty2012

TaeYoung Kim's starred repositories

pyro

Deep universal probabilistic programming with Python and PyTorch

Language:PythonApache-2.08458 200 1073

MarkovJunior

Probabilistic language based on pattern matching and constraint propagation, 153 examples

Language:C#MIT6940 93 27

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

Language:PythonMIT6939 136 463

GPU-Puzzles

Solve puzzles. Learn CUDA.

Language:Jupyter NotebookMIT5473 29 28

torchdiffeq

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

Language:PythonMIT5403 127 215

pytorch-optimizer

torch-optimizer -- collection of optimizers for Pytorch

Language:PythonApache-2.02997 33 63

knockknock

🚪✊Knock Knock: Get notified when your training ends with only two additional lines of code

Language:PythonMIT2773 65 41

PySR

High-Performance Symbolic Regression in Python and Julia

Language:PythonApache-2.02130 27 227

numpyro

Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

Language:PythonApache-2.02110 51 753

functorch

functorch is JAX-like composable function transforms for PyTorch.

Language:Jupyter NotebookBSD-3-Clause1383 28 520

pbdl-book

Welcome to the Physics-based Deep Learning Book (v0.2)

Language:Jupyter Notebook945 29 16

nflows

Normalizing flows in PyTorch

Language:PythonMIT818 29 49

normalizing-flows

PyTorch implementation of normalizing flow models

Language:PythonMIT653 14 41

geotorch

Constrained optimization toolkit for PyTorch

Language:PythonMIT641 9 35

backpack

BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.

Language:PythonMIT551 6 79

probnum

Probabilistic Numerics in Python.

Language:PythonMIT429 8 299

tinygp

The tiniest of Gaussian Process libraries

Language:PythonMIT283 9 69

pytorch_optimizer

optimizer & lr scheduler & loss function collections in PyTorch

Language:PythonApache-2.0215 6 57

stheno

Gaussian process modelling in Python

Language:PythonMIT213 10 17

TransformersCanDoBayesianInference

Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper

Language:Python177 15 3

Performance-Estimation-Toolbox

Code of the Performance Estimation Toolbox (PESTO) whose aim is to ease the access to the PEP methodology for performing worst-case analyses of first-order methods in convex and nonconvex optimization. The numerical worst-case analyses from PEP can be performed just by writting the algorithms just as you would implement them.

Language:MATLABMIT51 3 3