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09/22/2021
Learning Predictive and Interpretable Timeseries Summaries from ICU Data
Machine learning models that utilize patient data across time (rather th...
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02/09/2021
Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement
In representation learning, there has been recent interest in developing...
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02/02/2021
Evaluating the Interpretability of Generative Models by Interactive Reconstruction
For machine learning models to be most useful in numerous sociotechnical...
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11/04/2019
Ensembles of Locally Independent Prediction Models
Many ensemble methods encourage their constituent models to be diverse, ...
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06/10/2019
Tackling Climate Change with Machine Learning
Climate change is one of the greatest challenges facing humanity, and we...
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09/29/2018
Training Machine Learning Models by Regularizing their Explanations
Neural networks are among the most accurate supervised learning methods ...
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06/22/2018
Learning Qualitatively Diverse and Interpretable Rules for Classification
There has been growing interest in developing accurate models that can a...
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05/29/2018
Human-in-the-Loop Interpretability Prior
We often desire our models to be interpretable as well as accurate. Prio...
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11/26/2017
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients
Deep neural networks have proven remarkably effective at solving many cl...
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03/10/2017