Automating the Design of Chemical Compounds and Reactions Optimizing Expensive Objective Functions Sequential Decision Making for Computer Numerical Control (CNC) Manufacturing Accelerating and Improving Approximate Inference Generative Modeling for Computer Aided Design Rethinking Automatic Differentiation for Machine Learning Learning to Solve Partial Differential Equations Machine Learning and Science Understanding and Architecting Deep Neural Networks Data-Driven Design of Mechanical Meta-Materials
Automating the Design of Chemical Compounds and Reactions Optimizing Expensive Objective Functions Sequential Decision Making for Computer Numerical Control (CNC) Manufacturing Accelerating and Improving Approximate Inference Generative Modeling for Computer Aided Design Rethinking Automatic Differentiation for Machine Learning Learning to Solve Partial Differential Equations Machine Learning and Science Understanding and Architecting Deep Neural Networks Data-Driven Design of Mechanical Meta-Materials
