Analysis of deep neural networks for pixel processing — part One By Dawood Sheik, Abhishek Chaurasia, Eugenio Culurciello We measured the performance of the following bounding box detectors on...

Analysis of deep neural networks By Alfredo Canziani, Thomas Molnar, Lukasz Burzawa, Dawood Sheik, Abhishek Chaurasia, Eugenio Culurciello This are updated figure from the paper: An Analysis of...

Notes on Transformer neural network for sequence to sequence learning This post are notes to understand sequence-to-sequence (s2s) neural networks and in particular the Transformer neural network...

The fall of RNN / LSTM We fell for Recurrent neural networks (RNN), Long-short term memory (LSTM), and all their variants. Now it is time to drop them! It is the year 2014 and LSTM and RNN mak...

Tracking with deep networks Tracking is the process of locating a user selected object in different frames as it moves around the scene. It has a variety of uses such as human-computer interaction...

You are the product Social networks and mind games: ethical concerns and ideas for proper usage from: https://www.nuvi.com/blog/2017-social-trends-facebook-fake-news-and-instant-articles/ ...

Artificial Intelligence, AI in 2018 and beyond Or how machine learning is evolving into AI These are my opinions on where deep neural network and machine learning is headed in the larger fi...

2017: an year in review How we can raise again from the lowest lows in 2018 and later~ This year 2017 was a strange year. I tried to spend a great deal of time trying to understand what made thi...

Predictive neural networks for reinforcement learning By Lukasz Burzawa, Abhishek Chaurasia and Eugenio Culurciello We used predictive neural network like CortexNet to show that they can spee...

Learning and performing in the real world AKA Reinforcement Learning In order to interact with a complex environment, living entities need to produce a “correct” sequence of actions to achieve...