research
∙
09/26/2022
Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design
The efficient exploration of chemical space to design molecules with int...
share
research
∙
12/14/2020
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Distribution shifts can cause significant degradation in a broad range o...
research
∙
02/28/2020
The importance of transparency and reproducibility in artificial intelligence research
In their study, McKinney et al. showed the high potential of artificial ...
research
∙
01/21/2019
Calibration with Bias-Corrected Temperature Scaling Improves Domain Adaptation Under Label Shift in Modern Neural Networks
Label shift refers to the phenomenon where the marginal probability p(y)...
research
∙
10/31/2018
TF-MoDISco v0.4.4.2-alpha: Technical Note
TF-MoDISco (Transcription Factor Motif Discovery from Importance Scores)...
research
∙
07/26/2018
Computationally Efficient Measures of Internal Neuron Importance
The challenge of assigning importance to individual neurons in a network...
research
∙
02/20/2018
Learning to Abstain via Curve Optimization
In practical applications of machine learning, it is often desirable to ...
research
∙
04/10/2017
Learning Important Features Through Propagating Activation Differences
The purported "black box"' nature of neural networks is a barrier to ado...
research
∙
05/05/2016
