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PaulZhangIsing
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Official pytorch implementation of Action-GPT
提取微信聊天记录，将其导出成HTML、Word、Excel文档永久保存，对聊天记录进行分析生成年度聊天报告，用聊天数据训练专属于个人的AI聊天助手
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
LAVIS - A One-stop Library for Language-Vision Intelligence
PaCMAP: Large-scale Dimension Reduction Technique Preserving Both Global and Local Structure
Open standard for machine learning interoperability
Quantization of Convolutional Neural networks.
A corpus of meetings, with aligned pairs of transcriptions and reports
Layers Outputs and Gradients in Keras. Made easy.
GPU Accelerated t-SNE for CUDA with Python bindings
LocNet: Improving Localization Accuracy for Object Detection
Semantic SLAM using ROS, ORB SLAM, PSPNet101
Robust Out-of-distribution Detection in Neural Networks
A library for experimenting with, training and evaluating neural networks, with a focus on adversarial robustness.
This repository includes the official project of TransUNet, presented in our paper: TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.
Official tensorflow implementation for CVPR2020 paper “Learning to Cartoonize Using White-box Cartoon Representations”
Script to book badmin court on ActiveSG website.
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06
🌀 Stanford CS 228 - Probabilistic Graphical Models
How to train a TensorFlow Object Detection Classifier for multiple object detection on Windows
A paper list of object detection using deep learning.
Implementation for the paper (CVPR Oral): High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks
This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence Functions by Pang Wei Koh and Percy Liang.
Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs