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Pytorch implementation for Domain Adaptive Remaining Useful Life Prediction with Transformer
The deep residual shrinkage network is a variant of deep residual networks.
About Code release for "Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy" (ICLR 2022 Spotlight), https://openreview.net/forum?id=LzQQ89U1qm_
Official implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting" (ICLR 2024 Spotlight), https://openreview.net/forum?id=JePfAI8fah
this code library is mainly about applying graph neural networks to intelligent diagnostic and prognostic.
Image-to-Image Translation in PyTorch
Keras Temporal Convolutional Network. Supports Python and R.
[CVPR22] Official Implementation of DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
AAAI 2025: BearLLM: A Prior Knowledge-Enhanced Bearing Health Management Framework with Unified Vibration Signal Representation
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation (TPAMI 2020)
Pytorch!!!Pytorch!!!Pytorch!!! Dynamic Convolution: Attention over Convolution Kernels (CVPR-2020)
This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the …
A PyTorch implementation of "CoAtNet: Marrying Convolution and Attention for All Data Sizes"
Sequence modeling benchmarks and temporal convolutional networks
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
Leveraging multiple deep learning models for fault diagnosis
A comprehensive repository for motor fault diagnosis experiments using the Paderborn Bearing Dataset. This project explores deep learning-based feature extraction, ensemble modeling (CNNs, Transfor…