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05/22/2023
Adversarial Nibbler: A Data-Centric Challenge for Improving the Safety of Text-to-Image Models
The generative AI revolution in recent years has been spurred by an expa...
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06/07/2021
Uncertainty Baselines: Benchmarks for Uncertainty Robustness in Deep Learning
High-quality estimates of uncertainty and robustness are crucial for num...
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11/25/2020
Large-scale machine learning-based phenotyping significantly improves genomic discovery for optic nerve head morphology
Genome-wide association studies (GWAS) require accurate cohort phenotypi...
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11/06/2020
Underspecification Presents Challenges for Credibility in Modern Machine Learning
ML models often exhibit unexpectedly poor behavior when they are deploye...
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06/19/2020
Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift
Covariate shift has been shown to sharply degrade both predictive accura...
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06/05/2020
Population-Based Black-Box Optimization for Biological Sequence Design
The use of black-box optimization for the design of new biological seque...
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06/06/2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
Modern machine learning methods including deep learning have achieved gr...
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01/16/2019
TensorFlow.js: Machine Learning for the Web and Beyond
TensorFlow.js is a library for building and executing machine learning a...
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12/18/2018
Avoiding a Tragedy of the Commons in the Peer Review Process
Peer review is the foundation of scientific publication, and the task of...
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12/17/2018
BriarPatches: Pixel-Space Interventions for Inducing Demographic Parity
We introduce the BriarPatch, a pixel-space intervention that obscures se...
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11/21/2018
Predicting Electron-Ionization Mass Spectrometry using Neural Networks
When confronted with a substance of unknown identity, researchers often ...
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10/16/2018
AutoGraph: Imperative-style Coding with Graph-based Performance
There is a perceived trade-off between machine learning code that is eas...
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11/22/2017
No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World
Modern machine learning systems such as image classifiers rely heavily o...
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08/12/2017
Direct-Manipulation Visualization of Deep Networks
The recent successes of deep learning have led to a wave of interest fro...
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11/28/2016
