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  • 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?

  • REMoDNaV: robust eye-movement classification for dynamic stimulation

    Authors: Asim H. Dar, Adina S. Wagner, Michael Hanke
    Submitted by adswa    
      Mean reproducibility score:   7.0/10   |   Number of reviews:   3
    Why should we attempt to reproduce this paper?

    In theory, reproducing this paper should only require a clone of a public Git repository, and the execution of a Makefile (detailed in the README of the paper repository at We've set up our paper to be dynamically generated, retrieving and installing the relevant data and software automatically, and we've even created a tutorial about it, so that others can reuse the same setup for their work. Nevertheless, we've for example never tried it out across different operating systems - who knows whether it works on Windows? We'd love to share the tips and tricks we found to work, and even more love feedback on how to improve this further.

  • Population structure and phenotypic variation of Sclerotinia sclerotiorum from dry bean (Phaseolus vulgaris) in the United States

    Authors: Kamvar ZN, Amaradasa BS, Jhala R, McCoy S, Steadman JR, Everhart SE
    DOI: 10.7717/peerj.4152
    Submitted by hub-admin    
      Mean reproducibility score:   6.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    This paper is reproduced weekly in a docker container on continuous integration, but it is also set up to work via local installs as well. It would be interesting to see if it's reproducible with a human operator who knows nothing of the project or toolchain.

    Tags: R make Docker
  • Bayesian determination of the effect of a deep eutectic solvent on the structure of lipid monolayers

    Authors: "McCluskey, Andrew R. and Sanchez-Fernandez, Adrian and Edler, Karen J. and Parker, Stephen C. and Jackson, Andrew J. and Campbell, Richard A. and Arnold, Thomas
    DOI: DOI
    Submitted by hub-admin    
      Mean reproducibility score:   8.5/10   |   Number of reviews:   2
    Why should we attempt to reproduce this paper?

    I believe this represents the only example of a reproducible paper from scattering data collected at Diamond Light Source (UK) and the Institute Laue-Langevin (France)

    Tags: Python make

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