Popular GitHub Repositories for Novel Class Discovery

? Papers & tech blogs by companies sharing their work on data science & machine learning in production.

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

Official PyTorch implementation of PTS/PSRN: Fast and efficient symbolic expression discovery through parallelized tree search. Evaluates millions of expressions simultaneously on GPU with automated subtree reuse.

Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

[CVPR 2024] 4D Gaussian Splatting for Real-Time Dynamic Scene Rendering

Zero-1-to-3: Zero-shot One Image to 3D Object (ICCV 2023)

Data & AI Notebook templates catalog organized by tools, following the IMO (input, model, output) framework for easy usage and discovery..

文本挖掘和预处理工具（文本清洗、新词发现、情感分析、实体识别链接、关键词抽取、知识抽取、句法分析等），无监督或弱监督方法

Machine Learning University: Accelerated Natural Language Processing Class

Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)

Zero shot vulnerability discovery using LLMs

Message Passing Neural Networks for Molecule Property Prediction

NestJS Helper + AI Chatbot Development

[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

"AI-Researcher: Fully-Automated Scientific Discovery with LLM Agents" & "Open-Sourced Alternative to Google AI Co-Scientist"

PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.

novel deep learning research works with PaddlePaddle

Machine Learning University: Accelerated Computer Vision Class