Proceedings of the AAAI Conference on Artificial Intelligence • Vol 37 • No 8
Mixture Manifold Networks: A Computationally Efficient Baseline for Inverse Modeling
June 2023 • Gregory P. Spell, Simiao Ren, Leslie M. Collins, Jordan M. Malof
We propose and show the efficacy of a new method to address generic inverse problems. Inverse modeling is the task whereby one seeks to determine the hidden parameters of a natural system that produce a given set of observed measurements. Recent work has shown impressive results using deep learning, but we note that there is a trade-off between model performance and computational time. For some applications, the computational time at inference for the best performing inverse modeling method may be overly prohibiti…