birajaghoshal Goto Github PK

deep_active_learning

Implementation of active learning features for AxonDeepSeg software (axon-myelin segmentation)

deep_learning

Deep Learning Package in Python Based on The Deep Learning Tutorials and Theano

deep_learning_prediction_intervals

Code from the paper 'High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach'

deep_learning_projects

deep_mahalanobis_detector

Code for the paper "A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks".

deeplearning.ai

deeplearning.ai , By Andrew Ng, All slide and notebook + data (without solution) and video link

deeplearning.ai-summary

This repository contains my personal notes and summaries on [DeepLearning.ai](deeplearning.ai) course. I've enjoyed every little bit of the course hope you enjoy my notes too.

deeplift

Public facing deeplift repo

deepmedic

Efficient Multi-Scale 3D Convolutional Neural Network for Brain Lesion Segmentation

deepmetabolism

DeepMetabolism is a deep learning algorithm to predict phenotype from genome sequencing

deeppolyp

Work on deep learning for polyp characterization

deepprofile

DeepProfile framework, which learns a variational autoencoder (VAE) network from a vast quantity of publicly available gene expression samples and uses the learned network to encode a low-dimensional representation (LDR) for predicting complex phenotypes

deeppy

Deep learning in Python

deepslide

Code for the Nature Scientific Reports paper "Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks." A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images.

deepstats

Repository for "Known Unknowns: Uncertainty Quality in Bayesian Neural Networks" paper.

dementia-progression-analysis

Multi-level classification of dementia progression in MRIs with transfer learning

dhaka

diabetic

Repository contains my NIH research work: diabetic retinopathy detection using deep learning

dicom4miccai-handson

Supporting materials for the MICCAI 2017 DICOM tutorial

discrete-continuous-bdl

discriminativeactivelearning

Code and website for DAL (Discriminative Active Learning) - a new active learning algorithm for neural networks in the batch setting.

disease-detection

distance-metric-learning---cuhk03-dataset

This repository contains the results for my second Pattern Recognition Coursework that I completed with my partner Karoly. The report describes person re-ID experiments on the popular CUHK03 dataset that contains pictures of pedestrians taken from two different surveillance cameras. A set of features was already provided. The goal is to find a suitable distance metric which learns a feature transformation yielding improved performance on a range of metrics for kNN-retrieval. The original covariance based Mahalanobis method, Large Margin Nearest Neighbour Distance Metric, Metric Learning for Kernel Regression and a fully connected Neural Network with Triplet Loss are considered for this purpose. The Kernel Regression gave the best results with a performance similar to the untransformed baseline approach.

dl-uncertainty

What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?

dlgp-dr-diagnosis

Code of the experiments reported in Hybrid Deep Learning Gaussian Process for Diabetic Retinopathy Diagnosis and Uncertainty Quantification

dlproject

cs682

dropout-as-a-bayesian-approximation

Project for the course "Statistique bayésienne" at ENSAE - Representing Model Uncertainty in Deep Learning

dropouts

PyTorch Implementations of Dropout Variants

dropoutuncertaintyexps

Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"

dsb17-walkthrough

An end-to-end walkthrough of the winning submission by grt123 for the Kaggle Data Science Bowl 2017