Advancing fundamental science with Machine Learning at DeepMind

  • Online Seminar of the NOMAD Laboratory
  • Date: Mar 25, 2021
  • Time: 14:15
  • Speaker: James Kirkpatrick
  • Research Scientist at Google DeepMind, London, UK
  • Location: https://us02web.zoom.us/j/84322838289?pwd=MXYyTk9sRmdjVC9JalJBN0pBQ0k1dz09
  • Room: Meeting ID: 843 2283 8289 I Passcode: NOMAD
  • Host: NOMAD Laboratory
Advancing fundamental science with Machine Learning at DeepMind
Deep learning has had a transformative impact in computer science and is recently being applied to the natural sciences. In this talk, I will give an overview of recently published work on applying Machine Learning techniques to fundamental science problems at DeepMind. I will cover: super-human Quantum Dot tuning, advances in quantum Monte Carlo with neural network ansatz, transfer learning for predicting experimental material properties, and finally, touch upon recent advances in protein structure prediction. These case studies will hopefully allow me to exemplify the three kinds of impact that we can expect in future years: automating the experimental research pipeline, exploiting the representation power of neural network as function forms and finally extracting knowledge from data.
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