The docker-compose files for setting up a SearXNG instance with docker.

✨ AI Coding, Vim Style

Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

Best transfer learning and domain adaptation resources (papers, tutorials, datasets, etc.)

Awesome Incremental Learning

(TPAMI 2024) A Survey on Open Vocabulary Learning

Out-of-distribution detection, robustness, and generalization resources. The repository contains a curated list of papers, tutorials, books, videos, articles and open-source libraries etc

A curated list of papers & resources linked to open set recognition, out-of-distribution, open set domain adaptation and open world recognition

An awesome paper list of Semi-Supervised Learning under realistic settings.

CUDA Python: Performance meets Productivity

Paper List for Contrastive Learning for Natural Language Processing

LLM inference in C/C++

CodeBERT

[EMNLP 2021] SimCSE: Simple Contrastive Learning of Sentence Embeddings https://arxiv.org/abs/2104.08821

(ICCV 2023) Parametric Classification for Generalized Category Discovery: A Baseline Study

Code for TMLR 2023 paper "OpenCon: Open-world Contrastive Learning"

2024 up-to-date list of DATASETS, CODEBASES and PAPERS on Multi-Task Learning (MTL), from Machine Learning perspective.

Methods and Implements of Deep Clustering

Small, fast and powerful console music player for Unix-like operating systems.

Deep Clustering for Unsupervised Learning of Visual Features

Official implementation of "A Unified Objective for Novel Class Discovery", ICCV2021 (Oral)

"OpenLDN: Learning to Discover Novel Classes for Open-World Semi-Supervised Learning" by Mamshad Nayeem Rizve, Navid Kardan, Salman Khan, Fahad Shahbaz Khan, Mubarak Shah (ECCV 2022)

Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

The best ChatGPT that $100 can buy.

[TMLR] A curated list of language modeling researches for code (and other software engineering activities), plus related datasets.

Project Page for "LISA: Reasoning Segmentation via Large Language Model"