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researcher

A. Forbes

22 papers hereh-index 221.6k citations142 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author5
  • last author14

Across the 21 of 22 papers where every author was matched, so the position is known.

fields
  • cs.HC6
  • astro-ph.IM3
  • cs.GR3
  • astro-ph.CO2
  • astro-ph.GA2
  • cs.CL2
same name
  • A. Forbes — 93 papers, h 64
  • A. Forbes — 5 papers, h 16
  • A. Forbes — 4 papers, h 25
  • A. Forbes — 3 papers, h 3
  • A. Forbes — 2 papers, h 1
  • A. Forbes — 2 papers, h 6

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172025
most citedDisentangling the Cosmic Web Towards FRB 190608

57 citations · 187 across the 18 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

q-bio.QM2019

RuleVis: Constructing Patterns and Rules for Rule-Based Models

David Abramov, Jasmine Otto, Mahika Dubey +4

We introduce RuleVis, a web-based application for defining and editing "correct-by-construction" executable rules that model biochemical functionality, which can be used to simulat…

cs.MS2019

Solving Polynomial Systems with phcpy

Jasmine Otto, Angus Forbes, Jan Verschelde

The solutions of a system of polynomials in several variables are often needed, e.g.: in the design of mechanical systems, and in phase-space analyses of nonlinear biological dynam…

cs.HC2019★ 5 cited

TempoCave: Visualizing Dynamic Connectome Datasets to Support Cognitive Behavioral Therapy

Ran Xu, Manu Mathew Thomas, Alex Leow +2

We introduce TempoCave, a novel visualization application for analyzing dynamic brain networks, or connectomes. TempoCave provides a range of functionality to explore metrics relat…

cs.GR2019★ 3 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…

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