RE•WORK Deep Learning Summit

In this workshop, we explore an emerging frontier of AI and machine learning research that goes beyond correlational data mining approaches, such as deep learning. In a large variety of challenging business and societal problems, from combating traffic congestion in urban metropolises, and delivering better quality healthcare and education, to improving the success rate of digital marketing and online campaigns, and modeling interventions that combat climate change, what is fundamentally necessary is integrating three types of reasoning by combining correlational, causal, and imagination-based models. Participants in this workshop will be introduced to a powerful class of modeling languages that extend deep learning through a three layer architecture that combines correlational (layer one), causal and interventional decisions (layer two), as well as counterfactual and imagination-based reasoning (layer three).

Most of deep learning is currently restricted to producing a statistical summarization of data, that is, they answer “What is” queries. For example, generative adversarial networks (GANs) can be trained to produce new samples from a given fixed distribution (e.g, new face images given a dataset of face images). We introduce novel and powerful new methods that can also answer “What-if” queries, as well as “Why” queries. Integrating the three fundamental modes of reasoning, from “What is” to “What if” and “Why”, will enable the next generation of AI systems to be far more powerful than current deep learning architectures, like GANs. The workshop presentation will include a detailed overview of the underlying modeling languages, as well as hands-on demonstrations of how to use these new emerging tools in a diverse range of practical real-world problems.