faisalml
Mahmood Lab @ Brigham and Women's Hospital | Dana-Farber Cancer Institute | Harvard Medical School
Harvard Medical SchoolBoston, MA
Pinned Repositories
deep-learning-colonoscopy
Review in Deep Learning for Polyp Detection and Classification in Colonoscopy.
DeepLSR
Deep Learning-based Laser Speckle Reduction
Delving-deep-into-GANs
:mag: A curated list of Generative Adversarial Networks (GANs) resources sorted by reputation
FuseNet_PyTorch
Joint scene classification and semantic segmentation with FuseNet
GANPOP_Pytorch
GANPOP: Generative Adversarial Network Prediction of Optical Properties from Single Snapshot Wide-field Images
GeoNet
Code for GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose (CVPR 2018)
harmony
Fast, sensitive and accurate integration of single-cell data with Harmony
NCRF
Cancer metastasis detection with neural conditional random field (NCRF)
pytorch-cnn-visualizations
Pytorch implementation of convolutional neural network visualization techniques
CLAM
Data-efficient and weakly supervised computational pathology on whole slide images - Nature Biomedical Engineering
faisalml's Repositories
faisalml/DeepLSR
Deep Learning-based Laser Speckle Reduction
faisalml/Delving-deep-into-GANs
:mag: A curated list of Generative Adversarial Networks (GANs) resources sorted by reputation
faisalml/pytorch-cnn-visualizations
Pytorch implementation of convolutional neural network visualization techniques
faisalml/deep-learning-colonoscopy
Review in Deep Learning for Polyp Detection and Classification in Colonoscopy.
faisalml/GANPOP_Pytorch
GANPOP: Generative Adversarial Network Prediction of Optical Properties from Single Snapshot Wide-field Images
faisalml/NCRF
Cancer metastasis detection with neural conditional random field (NCRF)
faisalml/FuseNet_PyTorch
Joint scene classification and semantic segmentation with FuseNet
faisalml/GeoNet
Code for GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose (CVPR 2018)
faisalml/harmony
Fast, sensitive and accurate integration of single-cell data with Harmony