Inverse problems are ubiquitous in science, medicine, and engineering,and research in this area has produced real-world impact in medical tomography, seismic imaging, computational photography, and other domains. The recent rapid progress in learning-based image generation raises exciting opportunities in inverse problems, and this workshop seeks to gather a diverse set of participants who apply machine learning to inverse problems, from mathematicians and computer scientists to physicists and biologists. This gathering will facilitate new collaborations and will help develop more effective, reliable, and trustworthy learning-based solutions to inverse problems.