Probabilistic Deep Learning: Foundations, applications and open problems.
Event details
| Date | 31.10.2018 |
| Hour | 10:30 › 11:30 |
| Speaker | Dr. Danilo Rezende |
| Location | |
| Category | Conferences - Seminars |
Advances in deep generative models are at the forefront of deep learning research because of the promise they offer for allowing data-efficient learning, and for model-based reinforcement learning. In this talk I’ll review the foundations of probabilistic reasoning and generative modeling. I will then introduce modern approximations which allow for efficient large-scale training of a wide variety of generative models, demonstrate a few applications of these models to density estimation, missing data imputation, data compression and planning. Finally, I will discuss some of the open problems in the field.
Practical information
- Informed public
- Free
Organizer
- IPG Seminar (Olivier Lévêque)
Contact
- Dr Rezende is hosted by Prof. Wulfram Gerstner [email protected]