Topic: Controllability

Fatih Porikli examines why scaling image models alone does not guarantee visually correct results. He discusses separating scene planning from rendering, improving controllability and editing, and bringing high-resolution generation to edge devices, including the role of training objectives and reinforcement learning.

Neural circuits exhibit complex activity patterns, both spontaneously and in response to external stimuli. Information encoding and learning in neural circuits depend on the ability of time-varying stimuli to control spontaneous network activity. In particular, variability arising from the sensitivity to initial conditions of recurrent cortical circuits can limit the information conveyed about the sensory input. Spiking and firing rate network models can exhibit such sensitivity to initial conditions that are reflected in their dynamic entropy rate and attractor dimensionality computed from th