Pinned Repositories
NECARE
NEtwork-based CAncer gene RElationship prediciton
ProNAhot
ProNAhot: Predicting protein-DNA, protein-RNA and protein-protein binding hot-spots from sequence
RNAediting_Pipeline
BEHRT
Code for BEHRT: Transformer for Electronic Health Records
biLSTM_attn
chronological-map-phenotypes
Machine-readable version of electronic health record phenotypes for Kuan V. and Denaxas S. et al.
Compact-Transformers
[Preprint] Escaping the Big Data Paradigm with Compact Transformers, 2021
CRC_scRNAseq
DNABERT
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
Graph-Convolutional-Transformer
JiajunQiu's Repositories
JiajunQiu/VaDeSCEHR
JiajunQiu/ml-visuals
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
JiajunQiu/UKB_EHR_parser
JiajunQiu/Tools-to-Design-or-Visualize-Architecture-of-Neural-Network
Tools to Design or Visualize Architecture of Neural Network
JiajunQiu/youtube-ad-skip
JiajunQiu/Compact-Transformers
[Preprint] Escaping the Big Data Paradigm with Compact Transformers, 2021
JiajunQiu/vadesc
A probabilistic model to cluster survival data in a variational deep clustering setting
JiajunQiu/chronological-map-phenotypes
Machine-readable version of electronic health record phenotypes for Kuan V. and Denaxas S. et al.
JiajunQiu/CRC_scRNAseq
JiajunQiu/T5-learning-ICSE_2021
JiajunQiu/thefuck
Magnificent app which corrects your previous console command.
JiajunQiu/RNAediting_Pipeline
JiajunQiu/simpleT5
simpleT5 is built on top of PyTorch-lightning⚡️ and Transformers🤗 that lets you quickly train your T5 models.
JiajunQiu/NECARE
NEtwork-based CAncer gene RElationship prediciton
JiajunQiu/numpy-100
100 numpy exercises (with solutions)
JiajunQiu/scwat-st
Visium (10x Genomics) on human abdominal s.c white adipose tissue.
JiajunQiu/vae
a simple vae and cvae from keras
JiajunQiu/Graph-Convolutional-Transformer
JiajunQiu/Probabilistic-Deep-Learning-with-TensorFlow
Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of deep learning that aims to quantify the noise and uncertainty that is often present in real-world datasets.
JiajunQiu/nfnets-pytorch
NFNets and Adaptive Gradient Clipping for SGD implemented in PyTorch
JiajunQiu/ProNAhot
ProNAhot: Predicting protein-DNA, protein-RNA and protein-protein binding hot-spots from sequence
JiajunQiu/WGAN-for-RNASeq-analysis
A practical application of generative adversarial networks for RNA-seq analysis to predict the molecular progress of Alzheimer's disease
JiajunQiu/DNABERT
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
JiajunQiu/ncVarDB
Repo for the ncVAR database
JiajunQiu/BEHRT
Code for BEHRT: Transformer for Electronic Health Records
JiajunQiu/Matplotlib
Matplotlib超详细的案例和说明
JiajunQiu/LinkPredictionJJ
Implementation of different classes of link predictors and methods to assess and visualise their performance.
JiajunQiu/ResNet
Clean, scalable and easy to use ResNet implementation in Pytorch
JiajunQiu/NCBoost
Classifier of pathogenic non-coding variants in Mendelian diseases
JiajunQiu/GWA_tutorial
A comprehensive tutorial about GWAS and PRS