6.2k citations · 7k across the 18 of their papers we have counts for
4 papers · 1 filter
Grad-CAM: Why did you say that?
Ramprasaath R Selvaraju, Abhishek Das, Ramakrishna Vedantam +3
We propose a technique for making Convolutional Neural Network (CNN)-based models more transparent by visualizing input regions that are 'important' for predictions -- or visual ex…
Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models
Ashwin K Vijayakumar, Michael Cogswell, Ramprasath R. Selvaraju +4
Neural sequence models are widely used to model time-series data. Equally ubiquitous is the usage of beam search (BS) as an approximate inference algorithm to decode output sequenc…
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das +3
We propose a technique for producing "visual explanations" for decisions from a large class of CNN-based models, making them more transparent. Our approach - Gradient-weighted Clas…
Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles
Stefan Lee, Senthil Purushwalkam, Michael Cogswell +3
Many practical perception systems exist within larger processes that include interactions with users or additional components capable of evaluating the quality of predicted solutio…