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The repository is for safe reinforcement learning baselines.
JMLR: OmniSafe is an infrastructural framework for accelerating SafeRL research.
This repository contains the code and data accompanying the paper entitled "A Data-driven Multi-fidelity Physics-informed Learning Framework for Smart Manufacturing: A Composites Processing Case St…
GitHub's code repository is all you need
[TPAMI 2024] Awesome Resources of GNNs for Time Series Analysis (GNN4TS)
Curated tutorials and resources for Large Language Models, AI Painting, and more.
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
The official GitHub page for the survey paper "A Survey of Large Language Models".
Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond
This repo includes ChatGPT prompt curation to use ChatGPT and other LLM tools better.
Must-read Papers on Physics-Informed Neural Networks.
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06
Deep Residual Shrinkage Networks for Intelligent Fault Diagnosis（pytorch） 深度残差收缩网络应用于故障诊断
A playbook for systematically maximizing the performance of deep learning models.
Capsule network for fault diagnosis （胶囊网络用于故障诊断）
基于Laplace小波卷积和BiGRU的少量样本故障诊断方法 (Small sample fault diagnosis based on Laplace wavelet convolution and BiGRU)
Deep discriminative transfer learning network for cross-machine fault diagnosis
基于注意力机制的少量样本故障诊断 pytorch
Pytorch!!!Pytorch!!!Pytorch!!! Dynamic Convolution: Attention over Convolution Kernels (CVPR-2020)
This is an unofficial implementation of BOAT: Bilateral Local Attention Vision Transformer
The official implementation of ELSA: Enhanced Local Self-Attention for Vision Transformer
Official code of ICCV2021 paper "Residual Attention: A Simple but Effective Method for Multi-Label Recognition"
Codes for TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localization.