Friday, September 2, 2022, 11:00 am — Hybrid: Bldg. 510, Large Seminar Room
Abstract: It was recently proposed that neural networks could be used to approximate many-dimensional probability distributions that appear e.g. in lattice field theories or statistical mechanics. Subsequently they can be used as variational approximators to asses extensive properties of statistical systems, like free energy, and also as neural samplers used in Monte Carlo simulations. In this talk I will discuss two algorithms suitable for these purposes: Variational Autoregressive Networks and Normalizing Flows and present recent improvements.
Hosted by: Yoshitaka Hatta
Join Videoconference More Information
18016 | INT/EXT | Events Calendar
Not all computers/devices will add this event to your calendar automatically.
A calendar event file named "calendar.ics" will be placed in your downloads location. Depending on how your device/computer is configured, you may have to locate this file and double click on it to add the event to your calendar.
Event dates, times, and locations are subject to change. Event details will not be updated automatically once you add this event to your own calendar. Check the Lab's Events Calendar to ensure that you have the latest event information.