Brain and Cognitive Sciences Computational Tutorial Series

2017–2019

• Principles and Applications of Relational Inductive Biases in Deep Learning Kelsey Allen, MIT (April 11, 2019)
• Neural Decoding of Spike Trains and Local Field Potentials with Machine Learning in Python Omar Costilla Reyes, MIT (April 2, 2019)
• Bayesian Inference in Generative Models Luke Hewitt, MIT (November 13, 2018)           
• Unsupervised Discovery of Temporal Sequences in High-Dimensional Datasets Emily Mackevicius and Andrew Bahle, MIT (April 19, 2018)
• Dimensionality Reduction for Matrix- and Tensor-Coded Data (1 & 2) Alex Williams, Stanford (September 5, 2017)
• Calcium Imaging Data Cell Extraction Pengcheng Zhou, Columbia (July 12, 2017)
• Reinforcement Learning Sam Gershman, Harvard (June 16, 2017)
• Better Science Code Eric Denovellis, BU (May 10, 2017) 
• An Introduction to LSTMs in TensorFlow Harini Suresh and Nick Locascio, MIT (April 26, 2017) 
• An Introduction to Spike Sorting Jai Bhagat and Caroline Moore-Kochlacs, MIT (March 22, 2017)