CMU Artificial Intelligence Seminar Series sponsored by
Tuesday, Sep 21, 2021
Time: 12:00 - 01:00 PM ET
Kashif Rasul -- Modern Neural Probabilistic Forecasting
Relevant Paper(s):
- Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows
- Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting
Abstract: In this talk we will introduce the foundations of Neural Probabilistic Forecasting by reviewing its building blocks as well as some issues. We will then introduce how probabilistic forecasting works in this setting and talk about two recent papers which use Normalizing Flows and Energy based methods to tackle this problem.
Bio: Kashif Rasul is a Machine Learning Research scientist working on deep learning based methods and their applications at Morgan Stanley.