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An offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arxiv.org/abs/2211.14730
Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need (IJCV 2024)
Implemented ABSGD Algorithm in the Paper https://arxiv.org/abs/2012.06951
[CIKM 2022] Self-supervision Meets Adversarial Perturbation: A Novel Framework for Anomaly Detection (PyTorch)
📺 Discover the latest machine learning / AI courses on YouTube.
Code for "Few-Shot Learning by Dimensionality Reduction in Gradient Space"
implement of ICDE 2019 paper: Robust High Dimensional Stream Classification with Novel Class Detection
A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.
PyTorch implementation for the paper Class-incremental Novel Class Discovery (ECCV 2022)
A comprehensive survey on the time series domains
TOD: GPU-accelerated Outlier Detection via Tensor Operations
An Incremental Learning, Continual Learning, and Life-Long Learning Repository
PDFs and Codelabs for the Efficient Deep Learning book.
[ICLR 2022] Open-World Semi-Supervised Learning
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
自然语言处理领域下的相关论文（附阅读笔记），复现模型以及数据处理等（代码含TensorFlow和PyTorch两版本）
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
A monolingual and cross-lingual meta-embedding generation and evaluation framework
This repo is the official implementation of UPL (Unsupervised Prompt Learning for Vision-Language Models).
The official implementation of [CVPR2022] Decoupled Knowledge Distillation https://arxiv.org/abs/2203.08679 and [ICCV2023] DOT: A Distillation-Oriented Trainer https://openaccess.thecvf.com/content…
Code for Max-Margin Contrastive Learning - AAAI 2022
Summarize Massive Datasets using Submodular Optimization
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
🟠 A study guide to learn about Graph Neural Networks (GNNs)
List of papers, code and experiments using deep learning for time series forecasting
List of awesome papers about time series, mainly including algorithms based on machine learning | 收录时间序列分析中各个研究领域的高水平文章，主要包含基于机器学习的算法
Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order of magnitude using coresets and data selection.