wtj051

wtj051's Stars

• Nixtla/nixtla

  TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

  Language:Jupyter Notebook2.4k201

• Zeyu-Zhu/TFDSUNet

  TFDSUNet: Time-Frequency Dual-Stream Uncertainty Network for Battery SOH/SOC Prediction

  Language:Python417

• patrick-kidger/NeuralCDE

  Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)

  Language:Python63370

• jambo6/online-neural-cdes

  Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"

  Language:Python376

• xingyushu/FL_client_selection

  Federated learning client selection

  Language:Python181

• ikumpli/LSTM-GANS-RUL-Prediction-for-Lithium-ion-Bateries

  This paper summarizes a deep learning-based approach with an LSTM trained on the widely used Oxford battery degradation dataset and the help of generative adversarial networks (GANS).

  Language:Jupyter Notebook576

• BayesWatch/deep-kernel-transfer

  Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)

  Language:Python20230

• euphoria0-0/Active-Client-Selection-for-Communication-efficient-Federated-Learning

  Active Client Selection for Federated Learning

  Language:Python4114

• a280558071/IEDS_Planning

  Integrated Energy Distribution System Planning method, include a matlab version and a Python version

  Language:Jupyter Notebook357

• BeardHealth/Combined-Heat-and-Power-System-Economic-Dispatch

  Deep reinforcement learning approaches for CHP system economic dispatch

  Language:Python8219

• LucasNolasco/DeepDFML-NILM

  A new CNN architecture to perform detection, feature extraction, and multi-label classification of loads, in non-intrusive load monitoring (NILM) approaches, with a single model for high-frequency signals.

  Language:Jupyter Notebook334

• klemenjak/nilm-papers-with-code

  An archive for NILM papers with source code and other supplemental material

  13125

• thu-media/FedCL

  The implementation of "Continual Local Training for Better Initialization of Federated Models" (ICIP 2020).

  Language:Python171

• thinkenergy/dynamic_vae

  Dynamic VAE algorithm is used for anomaly detection of battery data

  Language:Python186

• HoochDeveloper/battery-aging

  Auto encoder for anomaly detection on battery data

  Language:Python32

• GiuTan/Weak-NILM

  Language:Python91

• xieck13/nilmtk-dl

  非侵入式负荷检测，一个很水的毕设

  Language:Jupyter Notebook191

• justsmart/DIMC

  Deep Double Incomplete Multi-view Multi-label Learning with Incomplete Labels and Missing Views

  Language:Python112

• UMDataScienceLab/Personalized_FL_with_DA

  The implementation of the paper domain adaptation for personalized federated learning

  Language:Python3

• nok-halfspace/Transformer-Time-Series-Forecasting

  Language:Python387102

• antoinedemathelin/wann

  Adversarial Weighting for Domain Adaptation in Regression

  Language:Jupyter Notebook223

• ChristoferNal/multi-nilm

  Multi-NILM: Multi Label Non Intrusive Load Monitoring

  Language:Python6820

• maxjcohen/transformer

  Implementation of Transformer model (originally from Attention is All You Need) applied to Time Series.

  Language:Jupyter Notebook864165

• karpathy/minGPT

  A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

  Language:Python20.8k2.7k

• maxencenoble/Differential-Privacy-for-Heterogeneous-Federated-Learning

  Differentially Private Federated Learning on Heterogeneous Data

  Language:Python5910

• wenzhu23333/Differential-Privacy-Based-Federated-Learning

  Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shakespeare, mnist, cifar-10 and fashion-mnist. )

  Language:Python35858

• sreyafrancis/BlockchainForFederatedLearning

  Democratize access to data, decentralize Artificial intelligence and enhance user privacy with Federated learning and Blockchain.

  Language:Python18329

• fangvv/VN-MADDPG

  Code for paper "基于多智能体深度强化学习的车联网通信资源分配优化"

  Language:Python21920

• TsingZ0/PFLlib

  37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 24 datasets. www.pfllib.com/

  Language:Python1.6k320

• Yangfan-Jiang/Federated-Learning-with-Differential-Privacy

  Implementation of dp-based federated learning framework using PyTorch

  Language:Python29057