Structure Estimation

Structure estimation focuses on inferring the underlying organizational patterns within data, aiming to reconstruct or represent these structures accurately. Current research emphasizes developing robust algorithms and model architectures, such as U-Former networks and iterative refinement methods, to handle complex scenarios like high-dimensional state spaces, noisy data (e.g., from blurred images or bandit feedback), and limited observability. These advancements are crucial for various applications, including 3D scene reconstruction, image deblurring, robotic perception, and causal inference, improving the accuracy and efficiency of these tasks.