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12/11/2020
TabTransformer: Tabular Data Modeling Using Contextual Embeddings
We propose TabTransformer, a novel deep tabular data modeling architectu...
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02/06/2020
Supervised Learning on Relational Databases with Graph Neural Networks
The majority of data scientists and machine learning practitioners use r...
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12/28/2019
SLM Lab: A Comprehensive Benchmark and Modular Software Framework for Reproducible Deep Reinforcement Learning
We introduce SLM Lab, a software framework for reproducible reinforcemen...
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12/06/2019
Sampling-Free Learning of Bayesian Quantized Neural Networks
Bayesian learning of model parameters in neural networks is important in...
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05/19/2019
Minimal Achievable Sufficient Statistic Learning
We introduce Minimal Achievable Sufficient Statistic (MASS) Learning, a ...
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11/13/2018
A General Method for Amortizing Variational Filtering
We introduce the variational filtering EM algorithm, a simple, general-p...
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10/25/2018
Some Requests for Machine Learning Research from the East African Tech Scene
Based on 46 in-depth interviews with scientists, engineers, and CEOs, th...
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10/18/2018
