Northern Lights Deep Learning Conference 2023
Title
AI for Science: Discovering diverse classes of equations in medicine and beyond
Abstract
Artificial Intelligence (AI) offers the promise of revolutionizing the way scientific discoveries are made and significantly accelerating their pace. This is important for numerous fields of study, including medicine. In this talk, I will present our research on AI for science over the past few years. I will start by briefly showing how we can discover closed-form prediction functions from cross-sectional data using symbolic metamodels. Then, I will introduce a new method, called D-CODE, which discovers closed-form ordinary differential equations (ODEs) from observed trajectories (longitudinal data).This method can only describe observable variables, yet many important variables in medical settings are often not observable. Hence, I will subsequently present the latent hybridisation model (LHM) that integrates a system of ODEs with machine-learned neural ODEs to fully describe the dynamics of the complex systems. However, ODEs are fundamentally inadequate to model systems with long-range dependencies or discontinuities. To solve these challenges, I will then present Neural Laplace, with which we can learn diverse classes of differential equations in the Laplace domain. I will conclude by presenting next research frontiers, including recent work on discovering partial differential questions from data (D-CIPHER). While these works are applicable in numerous scientific domains, in this talk I will illustrate the various works with examples from medicine, ranging from understanding cancer evolution to treating Covid-19.
This work is joint work with Zhaozhi Qian, Krzysztof Kacprzyk and Sam Holt.
Location and local date/time
This event will take place in person on January 10 at 8:30 GMT.
About the event
Deep learning is an emerging subfield in machine learning that has in recent years achieved state-of-the-art performance in image classification, object detection, segmentation, time series prediction and speech recognition to name a few. This conference will gather researchers both on a national and international level to exchange ideas, encourage collaborations and present cutting-edge research.
