most citedLearning Patterns in Sample Distributions for Monte Carlo Variance Reduction

3 citations · 6 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL20201 cited

Bio-inspired Structure Identification in Language Embeddings

Hongwei, Zhou, Oskar Elek +2

Word embeddings are a popular way to improve downstream performances in contemporary language modeling. However, the underlying geometric structure of the embedding space is not we…

astro-ph.IM20202 cited

Polyphorm: Structural Analysis of Cosmological Datasets via Interactive Physarum Polycephalum Visualization

Oskar Elek, Joseph N. Burchett, J. Xavier Prochaska +1

This paper introduces Polyphorm, an interactive visualization and model fitting tool that provides a novel approach for investigating cosmological datasets. Through a fast computat…

astro-ph.GA2020

Disentangling the Cosmic Web Towards FRB 190608

Sunil Simha, Joseph N. Burchett, J. Xavier Prochaska +12

FRB 190608 was detected by ASKAP and localized to a spiral galaxy at in the SDSS footprint. The burst has a large dispersion measure ( )…

astro-ph.GA2020

Revealing the Dark Threads of the Cosmic Web

Joseph N. Burchett, Oskar Elek, Nicolas Tejos +4

Modern cosmology predicts that matter in our Universe has assembled today into a vast network of filamentary structures colloquially termed the Cosmic Web. Because this matter is e…

cs.GR20193 cited

Learning Patterns in Sample Distributions for Monte Carlo Variance Reduction

Oskar Elek, Manu M. Thomas, Angus Forbes

This paper investigates a novel a-posteriori variance reduction approach in Monte Carlo image synthesis. Unlike most established methods based on lateral filtering in the image spa…