Rethinking Automatic Differentiation for Machine Learning Workloads
Accelerating and Improving Approximate Inference
Generative Modeling for Computer Aided Design
Learning to Solve Partial Differential Equations
Data-Driven Design of Mechanical Meta-Materials
Optimizing Expensive Objective Functions
Understanding Deep Neural Networks
Machine Learning for Design of Chemical Compounds and Reactions
