research
∙
12/19/2022
Natural Language to Code Generation in Interactive Data Science Notebooks
Computational notebooks, such as Jupyter notebooks, are interactive comp...
share
research
∙
05/01/2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness
Accurate uncertainty quantification is a major challenge in deep learnin...
research
∙
10/26/2021
Neural Program Generation Modulo Static Analysis
State-of-the-art neural models of source code tend to be evaluated on th...
research
∙
06/07/2021
Uncertainty Baselines: Benchmarks for Uncertainty Robustness in Deep Learning
High-quality estimates of uncertainty and robustness are crucial for num...
research
∙
10/19/2020
Combining Ensembles and Data Augmentation can Harm your Calibration
Ensemble methods which average over multiple neural network predictions ...
research
∙
05/14/2020
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors
Bayesian neural networks (BNNs) demonstrate promising success in improvi...
research
∙
02/17/2020
BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning
Ensembles, where multiple neural networks are trained individually and t...
research
∙
07/03/2019
Benchmarking Model-Based Reinforcement Learning
Model-based reinforcement learning (MBRL) is widely seen as having the p...
research
∙
02/21/2019
Interplay Between Optimization and Generalization of Stochastic Gradient Descent with Covariance Noise
The choice of batch-size in a stochastic optimization algorithm plays a ...
research
∙
03/12/2018
