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  • Southern Ocean deep mixing band emerges from a competition between winter buoyancy loss and upper stratification strength

    Authors: Romain Caneill, Fabien Roquet, and Jonas Nycander
    DOI: 10.5194/egusphere-2023-2404
    Submitted by rcaneill      
      Mean reproducibility score:   2.4/10   |   Number of reviews:   9
    Why should we attempt to reproduce this paper?

    I tried as hard as possible to make it reproducible, which it is on my computer. I would be happy to see if this still works on other computers. Moreover, by allowing easy reproducibility, I hope that other people may easily build research on top of this work.

  • The Polar Transition from Alpha to Beta Regions Set by a Surface Buoyancy Flux Inversion

    Authors: Romain Caneill Fabien Roquet Gurvan Madec Jonas Nycander
    DOI: 10.1175/JPO-D-21-0295.1
    Submitted by rcaneill      
      Mean reproducibility score:   0.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    I tried hard to make it reproducible, so hopefully this paper can serve as an example on how reproducibility can be achieved. I think that being reproducible with only few commands to type in a terminal is quite an achievment. At least in my field, where I usually see code published along with paper, but with almost no documentation on how to rerun it.

  • 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?

  • Finding Efficient Trade-offs in Multi-Fidelity Response Surface Modeling

    Authors: Sander van Rijn, Sebastian Schmitt, Matthijs van Leeuwen, Thomas Bäck
    Submitted by sjvrijn    
      Mean reproducibility score:   9.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    Because: - Two fellow PhDs working on different topics have been able to reproduce some figures by following the README instructions and I hope this extends to other people - I've tried to incorporate as many of the best practices as possible to make my code and data open and accessible - I've tried to make sure that my data is exactly reproducible with the specified random seed strategy - the paper suggests a method that should be useful to other researchers in my field, which is not useful unless my results are reproducible

  • Algorithm configuration data mining for CMA evolution strategies

    Authors: Sander van Rijn, Hao Wang, Bas van Stein, Thomas Bäck
    DOI: 10.1145/3071178.3071205
    Submitted by sjvrijn    
      Mean reproducibility score:   10.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    The original data took quite a while to produce for a previous paper, but for this paper, all tables and figures should be exactly reproducible by simply running the jupyter notebook.

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