YoVDO

Causal Representation Learning Through Multi-Modal Data Integration

Offered By: Broad Institute via YouTube

Tags

Causality Courses Data Science Courses Bioinformatics Courses Machine Learning Courses Statistical Inference Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore causal representation learning through multi-modal data integration in this 1-hour 17-minute workshop talk by Caroline Uhler from the Eric and Wendy Schmidt Center at the Broad Institute and MIT. Delivered as part of the Novo Nordisk Foundation Center Workshop on Multimodal Data Integration, the presentation delves into advanced techniques for integrating diverse data types to uncover causal relationships. Gain insights into cutting-edge approaches at the intersection of causality, machine learning, and multi-modal data analysis. Learn how these methods can be applied to complex biological systems and other domains requiring the synthesis of heterogeneous information sources.

Syllabus

NNFC Workshop: Caroline Uhler, Causal representation learning through multi-modal data integration


Taught by

Broad Institute

Related Courses

Epidemiology: The Basic Science of Public Health
The University of North Carolina at Chapel Hill via Coursera
Algorithmic Information Dynamics: From Networks to Cells
Santa Fe Institute via Complexity Explorer
Environmental Challenges: Human Impact in the Natural Environment
University of Leeds via FutureLearn
Data Analytics for Lean Six Sigma
University of Amsterdam via Coursera
Data Science: Inferential Thinking through Simulations
University of California, Berkeley via edX