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CliffordLai
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基于LangChain和ChatGLM-6B等系列LLM的针对本地知识库的自动问答
An easy/swift-to-adapt PyTorch-Lighting template. 套壳模板，简单易用，稍改原来Pytorch代码，即可适配Lightning。You can translate your previous Pytorch code much easier using this template, and keep your freedom to edit a…
收集AIOPS（智能运维），时间序列，异常检测，关联分析，告警收敛，根因分析，数据挖掘，机器学习，深度学习的学习资源。欢迎star。Collect learning resources for AIOPS (Intelligent Operation and Maintenance), time series, anomaly detection, correlation analysis,…
RSTutorials: A Curated List of Must-read Papers on Recommender System.
A distributed representation method for online logs.
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
An index of algorithms for learning causality with data
log anomaly detection toolkit including DeepLog
A robust streaming log template miner based on the Drain algorithm
Anomaly detection related books, papers, videos, and toolboxes
静默活体检测（Silent-Face-Anti-Spoofing）
Code for the IJCAI 2019 paper "Learning Shared Knowledge for Deep Lifelong Learning using Deconvolutional Networks" by Seungwon Lee, James Stokes, Eric Eaton
"Scalable and Order-robust Continual Learning with Additive Parameter Decomposition", ICLR 2020
Latex code for making neural networks diagrams
Implementation of [Progressive Neural Networks](https://arxiv.org/abs/1606.04671) using Pytorch Framework
CP and Tucker decomposition for Convolutional Neural Networks
A framework for data augmentation for 2D and 3D image classification and segmentation
PyTorch implementation of [1412.6553] and [1511.06530] tensor decomposition methods for convolutional layers.
Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet…
A technical report on convolution arithmetic in the context of deep learning
Open source release of the evaluation benchmark suite described in "Realistic Evaluation of Deep Semi-Supervised Learning Algorithms"
Evaluate three types of task shifting with popular continual learning algorithms.
The implementation code for Uncertainty-based Continual Learning with Adaptive Regularization (Neurips 2019)
Overcoming catastrophic forgetting with hard attention to the task