Pinned Repositories
phastimate
AttnSleep_fork
[IEEE TNSRE] "An Attention-based Deep Learning Approach for Sleep Stage Classification with Single-Channel EEG"
cleanrl
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
ERNIE
Official implementations for various pre-training models of ERNIE-family, covering topics of Language Understanding & Generation, Multimodal Understanding & Generation, and beyond.
iechub
Share learning resources.
lib_deduplicate
this version only write data to redis(no files)
Military_KG
A Military Knowledge Graph Using Baidu Relation Extraction Baseline System
MSCcodebase
The Midnight Scanning Club Codebase
Serving
A flexible, high-performance carrier for machine learning models（『飞桨』服务化部署框架）
tinysleepnet
TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG by Akara Supratak and Yike Guo from The Faculty of ICT, Mahidol University and Imperial College London respectively
hejieshi's Repositories
hejieshi/Military_KG
A Military Knowledge Graph Using Baidu Relation Extraction Baseline System
hejieshi/iechub
Share learning resources.
hejieshi/AttnSleep_fork
[IEEE TNSRE] "An Attention-based Deep Learning Approach for Sleep Stage Classification with Single-Channel EEG"
hejieshi/cleanrl
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
hejieshi/ERNIE
Official implementations for various pre-training models of ERNIE-family, covering topics of Language Understanding & Generation, Multimodal Understanding & Generation, and beyond.
hejieshi/lib_deduplicate
this version only write data to redis(no files)
hejieshi/MSCcodebase
The Midnight Scanning Club Codebase
hejieshi/Serving
A flexible, high-performance carrier for machine learning models（『飞桨』服务化部署框架）
hejieshi/tinysleepnet
TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG by Akara Supratak and Yike Guo from The Faculty of ICT, Mahidol University and Imperial College London respectively