Search Results for author:
Found 6 papers, 3 papers with code
Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models
We present our findings using publicly available chest pathologies (CheXpert, NIH ChestX-ray8) and COVID-19 datasets (BrixIA, and COVID-19 chest X-ray segmentation dataset).
Neural Response Interpretation through the Lens of Critical Pathways
Is critical input information encoded in specific sparse pathways within the neural network?
On Sparse Critical Paths of Neural Response
Is critical input information encoded in specific sparse paths within the network?
Rethinking Positive Aggregation and Propagation of Gradients in Gradient-based Saliency Methods
In this work, we empirically show that two approaches for handling the gradient information, namely positive aggregation, and positive propagation, break these methods.
Multiresolution Knowledge Distillation for Anomaly Detection
Unsupervised representation learning has proved to be a critical component of anomaly detection/localization in images.
Improving Feature Attribution through Input-specific Network Pruning
Attributing the output of a neural network to the contribution of given input elements is a way of shedding light on the black-box nature of neural networks.
