October 27, 2022 10:49

Abstract

The TrustML Young Scientist Seminars (TrustML YSS) started from January 28, 2022.

The TrustML YSS is a video series that features young scientists giving talks and discoveries in relation with Trustworthy Machine Learning.

Timetable for the TrustML YSS online seminars from Sep. to Oct. 2022.

For more information please see the following site.
TrustML YSS

This network is funded by RIKEN-AIP’s subsidy and JST, ACT-X Grant Number JPMJAX21AF, Japan.


【The 40th Seminar】


Date and Time: Nov. 1st 2:00 pm – 3:00 pm(JST)

Venue: Zoom webinar

Language: English

Speaker: Shinichi Nakajima (Technical University Berlin)
Title: Monte Carlo simulation of physical systems with deep generative models
Short Abstract
Deep learning has shown its usefulness in many fields of science. In this talk, we introduce our recent processes in Monte Carlo simulation in physics with deep generative models. Specifically, we extend our previous work, where we used generative models, e.g., autoregressive models and normalizing flows, that not only allow efficient sample generation but also provide the exact normalized sampling probability, and applied neural importance sampling for obtaining unbiased estimators. Our extension includes its application to estimating thermodynamic observables, such as free energy and entropy, in the lattice field theory, detection and mitigation of mode dropping, which can violates the condition for unbiasedness, and efficient training with path gradient estimators. Our experiments showed that our approaches can enhance the utility of deep generative models in physics, improve its reliability, and reduce the computational cost.


All participants are required to agree with the AIP Seminar Series Code of Conduct.
Please see the URL below.
https://aip.riken.jp/event-list/termsofparticipation/?lang=en

RIKEN AIP will expect adherence to this code throughout the event. We expect cooperation from all participants to help ensure a safe environment for everybody.


More Information

Date November 1, 2022 (Tue) 14:00 - 15:00
URL https://c5dc59ed978213830355fc8978.doorkeeper.jp/events/145820

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