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 filters, and more. All exercises incl
RLStructures is a library to facilitate the implementation of new reinforcement learning algorithms. It includes a library, a tutorial, and different RL algorithms provided as examples.
Deep Graph Library(DGL)은 기존의 DL 프레임워크(e.g. PyTorch, MXNet, Gluon 등)위에 그래프 뉴럴 네트워크 모델을 간편하게 구현하기 위한 Python 패키지입니다. DGL은 아키텍쳐 디자인 상에서 NetworkX의 API와 패러다임을 따르고 지향하고 있습니다.
TIGER is a Python toolbox to conduct graph vulnerability and robustness research. TIGER contains numerous state-of-the-art methods to help users conduct graph vulnerability and robustness analysis on graph structured data.
A Flax (Linen) implementation of ResNet (He, Kaiming, et al. 2015), ResNet-D (He, Tong et al. 2020), and ResNest (Zhang, Hang et al. 2020). The code is modular so you can mix and match the various stem, residual, and bottleneck im
Metatheory.jl is a general purpose metaprogramming and algebraic computation library for the Julia programming language, designed to take advantage of the powerful reflection capabilities to bridge the gap between symbolic mathema
This library contains JAX and Pytorch implementations of neural ODEs and Bayesian layers for stochastic variational inference. A rudimentary JAX implementation of differentiable SDE solvers is also provided, refer to torchsde [2]
Lambda Networks from the paper LambdaNetworks: Modeling Long-Range Interactions Without Attention by Bello et al. Adds support for Rank 3 and Rank 5 tensor inputs as well as initial implementation of ResNet-D with Lambda Convoluti
This repository provides a minimal implementation of adaptive gradient clipping (AGC) (as proposed in High-Performance Large-Scale Image Recognition Without Normalization1) in TensorFlow 2. The paper attributes AGC as a crucial co