There are no reviews yet. Be the first to send feedback to the community and the maintainers!
interpretAI_DigiPath
Hands-on Sessions 1 and 2 at the Building Interpretable AI for Digital Pathology AMLD workshop 2021concept_discovery_svd
Automatic identification of regions in the latent space of a model that correspond to unique concepts, namely to concepts with a semantically distinct meaning.interpretableWSItoRNAseq
An interpretable approach based on trainable attention that identifies which regions in H&E slides of colorectal cancer are the most informative about RNA transcriptomicsmiccaihackathon_shifts
XAI_evaluation
This repository contains the code and results of the paper "Evaluation and Comparison of CNN Visual Explanations for Histopathology", to be presented at the XAI Workshop at AAAI-21.InterpretabilityVISUM22
Hands-on session on Interpretable AI at the VISUM Summer School 2022multitask_adversarial
Repository for our work on multi task adversarial CNNsmedgift-VisBreastHist
Visual interpretability for patch-based classification of breast cancer histopathology images. (in review)intentionally_flawed_models
This repository contains the scripts to replicate the experiments in Interpreting Intentionally Flawed Models with Linear Probescam-toroidal-smooth-LSTMs
Improving Interpretability and Generalisation in Deep Learning. Thesis work for the MPhil in Machine Learning, Speech and Language Recognition at University of Cambridge, Engineering Department.cam-4M17-normApproximation
IMVIP2019
This reporitory contains the code for replicating the experiments in "Visualizing and interpreting feature reuse of pretrained CNNs for histopathology", submitted as a short abstract at IMVIP2019.cam-kaggle-ML-major
maragraziani.github.io
Personal Websitecam-4M17
medgift-KerasAugmentation
Improved Data Augmentation for CNN training with keras.tdd-bdd-final-project
Final project IBM introduction to TDD/BDD courseraintro-interpretableAI
Repository of the main source code for the assignments of the "Introduction to interpretable AI" courseLove Open Source and this site? Check out how you can help us