lsteffenel

lsteffenel's Stars

• edgeimpulse/expert-projects

  Language:PHP2914

• DepthAnything/Depth-Anything-V2

  Depth Anything V2. A More Capable Foundation Model for Monocular Depth Estimation

  Language:Python3.3k258

• LilianHollard/LeYOLO

  Language:Python15224

• agritechlab/RGBtoNDVI

  Language:Python21

• HPI-Information-Systems/S2Gpp

  Language:Rust4

• HPI-Information-Systems/s2gpp_experiments

  Experiments for Series2Graph++ Paper

  Language:Python3

• Qengineering/Jetson-Nano-Ubuntu-20-image

  Jetson Nano with Ubuntu 20.04 image

  69173

• labmlai/annotated_deep_learning_paper_implementations

  🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

  Language:Python53.8k5.6k

• PacktPublishing/Deep-Learning-with-fastai-Cookbook

  Deep Learning with fastai Cookbook, published by Packt

  Language:Jupyter Notebook5835

• bat67/pytorch-tutorials-examples-and-books

  PyTorch tutorials, examples and some books I found 【不定期更新】整理的PyTorch 最新版教程、例子和书籍

  Language:Jupyter Notebook1.1k272

• udlbook/udlbook

  Understanding Deep Learning - Simon J.D. Prince

  Language:Jupyter Notebook6.1k1.3k

• facebookresearch/segment-anything

  The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  Language:Jupyter Notebook46.7k5.5k

• facebookresearch/Kats

  Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

  Language:Python4.9k536

• fastai/fastbook

  The fastai book, published as Jupyter Notebooks

  Language:Jupyter Notebook21.5k8.3k

• max-sixty/aoc-gpt

  Solve Advent of Code puzzles with GPT-3

  Language:Python44027

• udacity/deep-learning-v2-pytorch

  Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

  Language:Jupyter Notebook5.3k5.3k

• tirthajyoti/Spark-with-Python

  Fundamentals of Spark with Python (using PySpark), code examples

  Language:Jupyter Notebook327263

• skywind3000/kcp

  :zap: KCP - A Fast and Reliable ARQ Protocol

  Language:C15.2k2.5k

• diego-vicente/som-tsp

  Solving the Traveling Salesman Problem using Self-Organizing Maps

  Language:Python3.7k577

• AI4SIM/model-collection

  This project contains a collection of deep learning models developed by the AI4Sim team with various partners. This is structured on the basis of use-cases providing canonical PyTorch Lightning pipelines allowing to train neural network models that are able to surrogate various physical processes.

  Language:Jupyter Notebook165

• kaelyavel/Rainnet-with-Ozone-data

  Project for CHPS Master

  Language:Jupyter Notebook1

• mogensen/docker-handson-training

  Language:CSS1211

• AGOberprieler/ginjinn

  Language:Python3

• melodyguan/enas

  TensorFlow Code for paper "Efficient Neural Architecture Search via Parameter Sharing"

  Language:Python1.6k390

• UoB-HPC/openmp-tutorial

  Exercises and Solutions for "Programming Your GPU with OpenMP: A Hands-On Introduction"

  Language:C11839

• FZJ-JSC/tutorial-multi-gpu

  Efficient Distributed GPU Programming for Exascale, an SC/ISC Tutorial

  Language:Cuda16550

• Yetangitu/cam

  Language:Shell11

• claudiafracca/BPSimpyLibrary

  Language:Python51

• edebrouwer/latentCCM

  Implementation of the Latent CCM paper

  Language:Python141

• pdeitel/IntroToPython

  Files associated with our book Intro to Python for Computer Science and Data Science

  310382