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9 software items. Page 1 of 1. 12 items per page. 1 filters active.
1-9 of 9

MATLAB scripts created during the work on "Multi-Δt approach for peak-locking error correction and uncertainty quantification in PIV"

MATLAB scripts created during the work on "Multi-Δt approach for peak-locking error correction and uncertainty quantification in PIV"

  • PIV (Particle Image Velocimetry)
  • Uncertainty Quantification
3
9

MATLAB scripts created during the work on "Design of experiments: a statistical tool for PIV uncertainty quantification"

MATLAB scripts created during the work on "Design of experiments: a statistical tool for PIV uncertainty quantification"

  • Design of Experiement (DOE)
  • Particle Image Velocimetry
  • systematic uncertainty
  • + 1
2
6

epistemic-bellman-operators

Epistemic Bellman Operators; code underlying the dissertation ‘Bayesian Model-Free Deep Reinforcement Learning’

  • Bayesian modelling
  • Deep Reinforcement Learning (DRL)
  • dynamic programming
  • + 2
  • Jupyter Notebook
  • Markdown
  • Python
1
1

Bayesian Ensembles for Exploration in Deep Reinforcement Learning; Code underlying the dissertation "Bayesian Model-Free Deep Reinforcement Learning"

Bayesian Ensembles for Exploration in Deep Reinforcement Learning; Code underlying the dissertation "Bayesian Model-Free Deep Reinforcement Learning"

  • Bayesian modelling
  • Deep Reinforcement Learning (DRL)
  • Ensemble model
  • + 2
  • Markdown
  • Python
1
0

Code accompanying the paper "Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model"

Code accompanying the paper "Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model"

  • data augmentation
  • deep ensembles
  • Machine learning
  • + 2
4
0

Code accompanying the paper "Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model" - VizDoom

Code accompanying the paper "Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model" - VizDoom

  • data augmentation
  • deep ensembles
  • Machine learning
  • + 2
4
0

Code accompanying the paper "Universal Value-Function Uncertainties"

Code accompanying the paper "Universal Value-Function Uncertainties"

  • deep ensembles
  • deep learning
  • Exploration
  • + 4
7
0

diverse-projection-ensembles

Code accompanying the paper "Diverse projection ensembles for distributional reinforcement learning"

  • deep learning
  • Distributional Reinforcement Learning
  • Exploration
  • + 4
  • Markdown
  • Other
  • Python
3
0

Sigma – Measurement Uncertainty Toolkit

Desktop application for measurement uncertainty analysis in accordance to JCGM 100:2008 and JCGM 101:2008 (GUM). Arbitrary measurement functions can be evaluated, and both independent and correlated input parameters are supported. Monte Carlo simulation is available for more complex models.

  • calibration
  • Measurement
  • measurement uncertainties
  • + 4
  • C
  • C++
  • CMake
  • + 2
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0