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researcher

N. Haut

10 papers hereh-index 555 citations24 works total

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

author position
  • first author6
  • middle author3
  • last author1

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • cs.NE6
  • cs.LG2
  • cs.CV1
  • nucl-th1

identity via Semantic Scholar / OpenAlex

activity
20222026
most citedCorrelation versus RMSE Loss Functions in Symbolic Regression Tasks

5 citations · 6 across the 10 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.NE2026

An Introduction and Tutorial for the Beagle Framework

Ilya Basin, Nathan Haut

The Beagle framework is a GPU-based genetic programming framework that enables highly efficient genetic programming search using large population sizes by leveraging NVIDIA GPUs. T…

cs.NE2026

The Effects of Population Size on the Performance of BEAGLE GPU-Based Genetic Programming Runs

Nathan Haut, Ilya Basin, Ruchika Gupta +4

The Beagle framework, through GPU-based Genetic Programming, enables population dynamics previously unattainable (within practical time frames) by CPU-constrained Genetic Programmi…

cs.CV2026

EvoIQA - Explaining Image Distortions with Evolved White-Box Logic

Ruchika Gupta, Illya Bakurov, Nathan Haut +1

Traditional Image Quality Assessment (IQA) metrics typically fall into one of two extremes: rigid, hand-crafted mathematical models or "black-box" deep learning architectures that…

cs.NE2026

GPU-Accelerated Genetic Programming for Symbolic Regression with Beagle Framework

Nathan Haut, Ilya Basin, Marzieh Kianinejad +4

Beagle is a new software framework that enables execution of Genetic Programming tasks on the GPU. Currently available for symbolic regression, it processes individuals of the popu…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.