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Jens Petersen

2 accepted papers

2024

Clockwork Diffusion: Efficient Generation With Model-Step Distillation

CVPR 2024highlight

This work aims to improve the efficiency of text-to-image diffusion models. While diffusion models use computationally expensive UNet-based denoising operations in every generation step we identify that not all operations are equally relevant for the final output quality. In particular we observe th…

2021

GP-ConvCNP: Better generalization for conditional convolutional Neural Processes on time series data

UAI 2021poster

Neural Processes (NPs) are a family of conditional generative models that are able to model a distribution over functions, in a way that allows them to perform predictions at test time conditioned on a number of context points. A recent addition to this family, Convolutional Conditional Neural Proce…