BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Institute of Statistical Research and Training - ECPv6.15.9//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://isrt.ac.bd
X-WR-CALDESC:Events for Institute of Statistical Research and Training
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:UTC
BEGIN:STANDARD
TZOFFSETFROM:+0000
TZOFFSETTO:+0000
TZNAME:UTC
DTSTART:20240101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=UTC:20250310T120000
DTEND;TZID=UTC:20250310T133000
DTSTAMP:20251026T083042
CREATED:20250306T035154Z
LAST-MODIFIED:20250306T035154Z
UID:7503-1741608000-1741613400@isrt.ac.bd
SUMMARY:Applied Statistics and Data Science Seminar on Monday March 10\, 2025
DESCRIPTION:Title: Variational Autoencoder Model for Exploring Latent Spaces in High-Dimensional Datasets \nVenue\, time and date: ISRT\, 12:15 pm\, March 10\, 2025 \nSpeaker: Mashfiqul Huq Chowdhury\, PhD\, Associate Professor at Mawlana Bhashani Science and Technology Deltin 7 Aviator গেম টাকা ইনকাম \nAbstract:  \nIn this talk\, I will focus on a probabilistic generative model known as the Variational Autoencoder (VAE). The VAE model uses variational Bayes to approximate the intractable posterior distribution over latent variables. I will begin by presenting the derivation of the evidence lower bound (ELBO) and then discuss the optimization procedure of the model. During training\, the VAE learns smooth latent space representations through regularization. This learning paradigm can be applied to various tasks\, including unsupervised clustering\, regression\, and the generation of new instances. To demonstrate its application\, I will showcase how the VAE model can be applied to high-dimensional datasets and highlight the results in terms of clustering performance and sample generation.
URL:https://isrt.ac.bd/event/applied-statistics-and-data-science-seminar-on-monday-march-10-2025/
CATEGORIES:seminar
END:VEVENT
END:VCALENDAR