Winnie Xu*, Michael Poli*, Stefano Masseroli*, Chenlin Meng, Kuno Kim, Stefano Ermon
We develop a new class of differentiable operators that leverage the underlying regularity of natural and artificial objects at various scales. Neural Collages are a class of implicit operators that discover self-similar representations of data and are efficient neural compressors, powerful decoders in deep generative models, and may be used towards various creative and artistic generations.
Neural Information Processing Systems (NeurIPS), 2022.