Facebook's Captum brings explainability to machine learning

Facebook today introduced Captum, a library for explaining decisions made by neural networks with deep learning framework PyTorch. Captum is designed to implement state of the art versions of AI models like Integrated Gradients, DeepLIFT, and Conductance. Captum allows researchers and developers to interpret decisions made in multimodal environments that combine, for example, text, images, and video, and allows them to compare results to existing models within the library. Developers can also use Captum to understand feature importance or perform a deep dive on neural networks to understand neuron and layer attributions. The tool will also launch with Captum Insights, a visualization tool for visual representations of Captum results.