We propose TabTransformer, a novel deep tabular data modeling architectu...
The majority of data scientists and machine learning practitioners use
r...
We introduce SLM Lab, a software framework for reproducible reinforcemen...
Bayesian learning of model parameters in neural networks is important in...
We introduce Minimal Achievable Sufficient Statistic (MASS) Learning, a
...
We introduce the variational filtering EM algorithm, a simple,
general-p...
Based on 46 in-depth interviews with scientists, engineers, and CEOs, th...
Machine learning models that take computer program source code as input
...