Recommender Systems: Exploring the Unknown Using Uncertainty
Learn what the exploration-exploitation tradeoff is, and how to use your model's uncertainty to explore new items in a wise manner.
Neural Networks from a Bayesian Perspective
Learn how to estimate model uncertainty in neural networks.
Using Uncertainty to Interpret your Model
Interpreting deep learning models is hard. Learn how to use uncertainty estimates to get insights about what the model has learned.
Neural Networks gone wild! They can sample from discrete distributions now!
Learn how to use Gumbel distribution to form a NN containing a discrete random component.
Deep Learning: Theory & Practice
Summary of TCE conference - "Deep Learning: Theory & Practice".
The Hitchhiker's Guide to Hyperparameter Tuning
Our implementation and usage of hyperparameter tuning at Taboola.
Word morphing
How to employ word2vec's embeddings and A* search algorithm to morph between words.
Gated Multimodal Units for Information Fusion
Learn how to train a neural network to use inputs from multiple different modalities using the GMU block.