Variational Autoencoder - How Asterix Pushes Data from High- to Low Dimensional Representation
- Date
- Jun 20, 2024
- Time
- 11:00 AM - 12:00 PM
- Speaker
- Jan Ewald, Nico Scherf
- Affiliation
- ScaDS.AI Dresden/Leipzig
- Series
- ScaDS.AI Lecture Series
- Language
- en
- Main Topic
- Informatik
- Description
- In the era of high-dimensional data in biomedical research and other application areas, representation learning and dimension reduction by deep learning networks have become a popular choice and vivid field of research. Variational Autoencoders (VAE) are probabilistic deep learning networks and their derivatives are promising solutions for explainable representation learning or cross-modal data integration. In our lecture we will touch the basics, show the application to molecular data in biomedical research and our latest framework development for the application of VAE to any data and research.
- Links
Last modified: Jun 13, 2024, 2:48:42 PM
Location
Online, please follow the internet link. (https://tud.link/i8zf )
Organizer
Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI)Chemnitzer Straße46b, 2. OG01187Dresden
- Phone
- +49 351 463-40900
- ScaDS.AI
- Homepage
- https://scads.ai
Scan this code with your smartphone and get directly this event in your calendar. Increase the image size by clicking on the QR-Code if you have problems to scan it.
Legend
- Biology
- Chemistry
- Civil Eng., Architecture
- Computer Science
- Economics
- Electrical and Computer Eng.
- Environmental Sciences
- for Pupils
- Law
- Linguistics, Literature and Culture
- Materials
- Mathematics
- Mechanical Engineering
- Medicine
- Physics
- Psychology
- Society, Philosophy, Education
- Spin-off/Transfer
- Traffic
- Training
- Welcome