5 papers
Multiscaling in Wasserstein Spaces
Wael Mattar, Nir Sharon
We present a novel multiscale framework for analyzing sequences of probability measures in Wasserstein spaces over Euclidean domains. Exploiting the intrinsic geometry of optimal t…
Geometric multiscale analysis via nonstationary subdivision schemes
Hadar Landau, Wael Mattar, Nir Sharon
Pyramid transforms are constructive methods for analyzing sequences in a multiscale fashion. Traditionally, these transforms rely on stationary upsampling and downsampling operatio…
Bias Reduction by Multiscale Quasi-Interpolation for Scalar- and Manifold-Valued Functions
Asaf Abas, Nir Sharon
We study the bias--variance tradeoff within a multiscale approximation framework. Our approach uses a given quasi-interpolation operator, which is repeatedly applied within an erro…
Wavelets Are All You Need for Autoregressive Image Generation
Wael Mattar, Idan Levy, Nir Sharon +1
In this paper, we take a new approach to autoregressive image generation that is based on two main ingredients. The first is wavelet image coding, which allows to tokenize the visu…
Efficient Trajectory Inference in Wasserstein Space Using Consecutive Averaging
Amartya Banerjee, Harlin Lee, Nir Sharon +1
Capturing data from dynamic processes through cross-sectional measurements is seen in many fields, such as computational biology. Trajectory inference deals with the challenge of r…