Neural Composition

Neural composition focuses on building complex systems or representations from simpler, reusable components, mirroring human cognitive processes. Current research emphasizes developing neural network architectures that can effectively combine these components, often using neural fields, program synthesis, or modular networks, to achieve tasks like image editing, scene generation, and action recognition. This approach offers improved efficiency, interpretability, and generalization capabilities compared to monolithic models, impacting diverse fields from computer vision and graphics to robotics and artificial intelligence. The ability to learn and recombine learned components promises more robust and adaptable AI systems.