Tomandjob

Tomandjob's Stars

• 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:Python57.6k4601325.9k

• KindXiaoming/pykan

  Kolmogorov Arnold Networks

  Language:Jupyter Notebook15.3k1124171.4k

• lss233/chatgpt-mirai-qq-bot

  🚀 一键部署！真正的 AI 聊天机器人！支持ChatGPT、文心一言、讯飞星火、Bing、Bard、ChatGLM、POE，多账号，人设调教，虚拟女仆、图片渲染、语音发送 | 支持 QQ、Telegram、Discord、微信 等平台

  Language:Python13.5k751.1k1.6k

• thuml/Time-Series-Library

  A Library for Advanced Deep Time Series Models.

  Language:Python7.6k775541.2k

• interpretml/interpret

  Fit interpretable models. Explain blackbox machine learning.

  Language:C++6.3k146453737

• PaddlePaddle/ERNIE

  Official implementations for various pre-training models of ERNIE-family, covering topics of Language Understanding & Generation, Multimodal Understanding & Generation, and beyond.

  Language:Python6.3k1956621.3k

• Blealtan/efficient-kan

  An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).

  Language:Python4.2k3543369

• facebookresearch/swav

  PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882

  Language:Python2k41116283

• thuml/TimesNet

  About Code release for "TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis" (ICLR 2023), https://openreview.net/pdf?id=ju_Uqw384Oq

  756102470

• GistNoesis/FourierKAN

  Language:Python7158759

• XifengGuo/DEC-keras

  Keras implementation for Deep Embedding Clustering (DEC)

  Language:Python4831032160

• liaoyuhua/LLM4TS

  Large Language & Foundation Models for Time Series.

  46616239

• marcopeix/time-series-analysis

  Collection of notebooks for time series analysis

  Language:Jupyter Notebook3721212122

• Tony607/Keras_Deep_Clustering

  How to do Unsupervised Clustering with Keras

  Language:Jupyter Notebook239813137

• Egrt/yolov7-obb

  在YOLOv7的基础上使用KLD损失修改为旋转目标检测yolov7-obb

  Language:Python18324627

• cloudtostreet/Sen1Floods11

  Language:Jupyter Notebook16781545

• AARG-FAN/Yolo_for_Wukong

  a simple project to beat boss in Blackmyth Wukong, using yolo8 to detect boss movement and a script to react to certain detections

  Language:Python13034

• xuyxu/Deep-Clustering-Network

  PyTorch Implementation of "Towards K-Means-Friendly Spaces: Simultaneous Deep Learning and Clustering," Bo Yang et al., ICML'2017.

  Language:Python1233429

• siddhartamukherjee/NEU-DET-Steel-Surface-Defect-Detection

  This project is about detecting defects on steel surface using Unet. The dataset used for this project is the NEU-DET database.

  Language:Jupyter Notebook981430

• samuelkim314/DeepSymReg

  Official repository for the paper "Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery"

  Language:Python696322

• neilfei/brivl-nmi

  Language:Python612510

• CVHub520/yolov5_obb

  Language:Python543611

• Tang1705/Happy-Reconstruction

  轮轨姿态反映着列车运行中轮与轨的接触关系，掌握高铁轮轨姿态是保障高铁安全运营的基础。基于计算机视觉技术的无接触方法可以通过采集运营状态下的轮轨图像，通过三维重建获取轮轨实时姿态。由于高铁运行速度快，轮轨表面光滑，给基于特征点提取的三维重建 (3D Reconstruction) 带来了极大挑战。本项目采用基于空间编码（Space Codification）的编码结构光（coded structured light）的方法，将单幅编码图案（one-shot）投影在轮轨表面，提高特征点的提取和识别精度，并将 De Bruijn 分析与小波变换（wavelet transform）分析相结合，增加了基于特征点的点云提取稠密度，从而实现了单次投影的点云稠密重建。项目完成了从半径95mm的球体提取17W条以上的点云 (Point Cloud) 数据，半径误差0.678mm，实现了对铁轨等多个物体的三维重建，完成了结构光三维重建软件开发，提供了基于主动视觉的三维重建和点云数据可视化展示、编辑的平台。

  Language:C++52439

• marcopeix/AppliedTimeSeriesForecastingInPython

  Repository with data, starter notebooks, and solution notebooks for my course Applied Time Series Forecasting in Python

  Language:Jupyter Notebook452017

• tamasino52/Railway_detection

  Railway detection in video without deep learning

  Language:Python401213

• tamasino52/Railroad_and_Obstacle_detection

  This program detect and identify obstacle on railway. If program detect some obstacle that train must stop, program gives you warning sign. This program Also estimate riskiness of obstacle how it is negligible or not. We provide many models to you to detect railways and obstacles.

  Language:Jupyter Notebook28255

• giuliamesc/BPINNs

  Language:Python24207

• HassanBinHaroon/deep-hough-transform

  This is the implementation of https://github.com/Hanqer/deep-hough-transform on Google Colab.

  Language:Jupyter Notebook13132

• zhouchunpong/multi-view-3DGPR

  The code and dataset of paper *Multi-View Fusion and Distillation for Subgrade Distresses Detection based on 3D-GPR*

  Language:Python10110

• tamasino52/Masking_Tool

  Segmentation masking tool using watershed transform.

  Language:Python1201