Category: Machine learning

California Sunrise

I’m currently visiting Santa Barbara for KITP Program: Machine Learning for Quantum Many-Body Physics. If you ever get an opportunity to go for one of the Kavli Institute programs, definitely definitely go. I will write more on science part later, for now just a few pictures of sunrises and sunsets I took while running.  

Machine learning blog at ETH

  The interest in possible applications of machine learning in physics has been growing exponentially for a while now and there seems to be a sea of literature. Couple of months ago we decided to review the literature and have weekly seminar about the papers we found interesting. There is a dedicated blog post for […]

New paradigm for parameter estimation

  In our latest work, now on arXiv, we show how to use a convolutional neural network to extract physical parameters (even the quantum ones!) from experimental currents. In my PhD I was generally concerned with monitoring and parameter estimation of quantum systems. These elements are crucial for efficiently functioning quantum devices, and, in difference from […]

Exporting histograms from TensorFlow

Lately I have been working a lot with Google’s TensorFlow library for machine learning. It has a really nice tool for data visualisation, TensorBoard, which can be very useful to understand how the training and evaluation of your model is working. One small bottleneck though is that it has a built-in tool for data export […]