Global Explanations of Neural Networks: Mapping the Landscape of Predictions

1 code implementation • 6 Feb 2019 • Mark Ibrahim, Melissa Louie, Ceena Modarres, John Paisley

A barrier to the wider adoption of neural networks is their lack of interpretability.

Mixed Membership Recurrent Neural Networks

no code implementations • 23 Dec 2018 • Ghazal Fazelnia, Mark Ibrahim, Ceena Modarres, Kevin Wu, John Paisley

Models for sequential data such as the recurrent neural network (RNN) often implicitly model a sequence as having a fixed time interval between observations and do not account for group-level effects when multiple sequences are observed.

Dynamic Topic Modeling

Towards Explainable Deep Learning for Credit Lending: A Case Study

no code implementations • 15 Nov 2018 • Ceena Modarres, Mark Ibrahim, Melissa Louie, John Paisley

Deep learning adoption in the financial services industry has been limited due to a lack of model interpretability.