Papers



Submit a Paper!

Browse ReproHack papers

  • Sensitivity and dimensionality of atomic environment representations used for machine learning interatomic potentials

    Authors: Berk Onat, Christoph Ortner and James Kermode
    DOI: 10.1063/5.0016005
    Submitted by jameskermode      

    Why should we attempt to reproduce this paper?

    Popular descriptors for machine learning potentials such as the Behler-Parinello atom centred symmetry functions (ACSF) or the Smooth Overlap of Interatomic Potentials (SOAP) are widely used but so far not much attention has been paid to optimising how many descriptor components need to be included to give good results.

  • PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals

    Authors: Henry Charlesworth and Giovanni Montana
    Submitted by gmontana74      
      Mean reproducibility score:   10.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    This paper proposes a probabilistic planner that can solve goal-conditional tasks such as complex continuous control problems. The approach reaches state-of-the-art performance when compared to current deep reinforcement learning algorithms. However, the method relies on an ensemble of deep generative models and is computationally intensive. It would be interesting to reproduce the results presented in this paper on their robotic manipulation and navigation problems as these are very challenging problems that current reinforcement learning methods cannot easily solve (and when they do, they require a significantly larger number of experiences). Can the results be reproduced out-of-the-box with the provided code?

  • model4you: An R Package for Personalised Treatment Effect Estimation

    Authors: Seibold, H., Zeileis, A. and Hothorn, T., 2019
    DOI: 10.5334/jors.219
    Submitted by hub-admin    
      Mean reproducibility score:   9.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    I guess it could be a cool learning experience. The paper is written with knitr, uses a seed, is part of the R package it describes, was openly written using version control (SVN, R-Forge) and is available in an open access journal (@up_jors).

    Tags: R LaTeX SVN knitr

Search for papers

Filter by tags

Python R GDAL GEOS GIS Shiny PROJ Galaxies Astronomy HPC Databases Binder Social Science Stata make Computer Science Jupyter Notebook tidyverse emacs literate earth sciences clumped isotopes org-mode geology eyetracking LaTeX Git ArcGIS Docker Drake SVN knitr C Matlab Mathematica Meta-analysis swig miniconda tensorflow keras Pandas SQL neuroscience robotics deep learning planner reiforcement learning Plasma physics Hybrid-PIC EPOCH Laser Gamma-ray X-ray radiation Petawatt Fortran plasma PIC physics Monte Carlo Atomistic Simulation LAMMPS Electron Transport DFT descriptors interatomic potentials machine learning Molecular Dynamics Python scripting AIRSS structure prediction density functional theory high-throughput machine-learning RNA bioinformatics CFD Fluid Dynamics OpenFOAM C++ DNS Mathematics Droplets Basilisk Particle-In-Cell psychology Stan Finance SAS Replication crisis Economics Malaria consumer behavior number estimation mental arithmetic psychophysics Archaeology Precipitation Epidemiology Parkrun Health Health Economics HTA plumber science of science Zipf networks city size distribution urbanism literature review Preference Visual Questionnaire Mann-Whitney Correlation Conceptual replication Cognitive psychology Multinomial processing tree (MPT) modeling #urbanism #R k-means cluster analysis city-regions Urban Knowledge Systems Topic modelling Planning Support Systems Software Citation Quarto snakemake Numerical modelling Ocean climate physical oceanography apptainer oceanography All tags Clear tags

Key

  Associated with an event
  Available for general review
  Public reviews welcome