〈 physics | machine learning 〉


Conference on Machine Learning and Physics at IASTU

IASTU Beijing hosts "Machine Learning and Physics" (July 4-6, 2018)

Program on Machine Learning for Quantum Many-Body Physics at KITP

KITP Santa Barbara announces a program on Machine Learning for Quantum Many-Body Physics (January 28 - March 22, 2019)

Workshop Machine Learning for Quantum Many-Body Physics at mpipks

mpipks Dresden hosts the workshop Machine Learning for Quantum Many-Body Physics (June 25-29, 2018)


The Theory of Deep Learning - Part I

Why do modern deep neural networks (DNNs) perform so well on previously unseen test data, even when their number of weights is much larger than the number of data ...

Machine Learning Topological Defects in the XY Model

One of the discoveries that earned the 2016 Nobel Prize was that topological effects play an important role in ...

Tensor Networks: Putting Quantum Wavefunctions into Machine Learning

Why tensor networks? If you follow machine learning, you have definitely heard of neural networks. If you are a physicist, ...


Meet the team of physicists contributing to this blog, working at the intersection of machine learning and quantum physics, across three institutes:
Perimeter Institute: leading research, training and outreach in foundational theoretical physics. The Flatiron Institute: advancing scientific research through computational methods. Vector Institute: driving excellence and leadership in knowledge, creation, and use of artificial intelligence.

These are the papers that we are reading, and the ideas that we are talking about.

    Roger Melko
    Miles Stoudenmire
    Anna Go
    Matt Beach