A game theoretic approach to explain the output of any machine learning model.

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…

A collection of infrastructure and tools for research in neural network interpretability.

MLOps examples

"Neural Turing Machine" in Tensorflow

Code and shared files

Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"

Mathematical consequences of orthogonal weights initialization and regularization in deep learning. Experiments with gain-adjusted orthogonal regularizer on RNNs with SeqMNIST dataset.