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NeurIPS-2019 Reproducibility Challenge

Accepted reports of the NeurIPS 2019 Reproducibility Challenge, conducted in OpenReview, to be published in ReScience Journal.

Directory information

Directories are created using the citation keys of the following reports. Every directory contains two subfolders:

  • openreview : Contains the files submitted by authors to OpenReview
  • journal : Contains the ReScience C Template files which is modified according to the paper. All modifications should be done here.

Papers

  • Alacchi, G., Lam, G. & Perreault-Lafleur, C. [Re] Unsupervised State Representation Learning in Atari. Compiled File, Folder DOI
  • Ferles, A., Nöu, A. & Valavanis, L. [Re] Zero-Shot Knowledge Transfer via Adversarial Belief Matching. Compiled File, Folder DOI
  • Garg, A. & Kagi, S. S. [Re] Hamiltonian Neural Networks. Compiled File, Folder DOI
  • Gohil, V., Narayanan, S. D. & Jain, A. [Re] One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers. Compiled File, Folder DOI
  • Kviman, O., Nilsson, L. & Larsson, M. [Re] Tensor Monte Carlo Particle Methods for the GPU Era. Compiled File, Folder DOI
  • Liljefors, F., Sorkhei, M. M. & Broomé, S. [Re] Unsupervised Scalable Representation Learning for Multivariate Time Series. Compiled File, Folder DOI
  • Liu, Y., Xu, J. & Pan, Y. [Re] When to Trust Your Model: Model-Based Policy Optimization. Compiled File, Folder DOI
  • Matosevic, A., Hein, E. & Nuzzo, F. [Re] Generative Modeling by Estimating Gradients of the Data Distribution. Compiled File, Folder DOI
  • Nayak, N., Raj, V. & Kalyani, S. [Re] A comprehensive study on binary optimizer and its applicability. Compiled File, Folder DOI
  • Singh, A. & Bay, A. [Re] On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks. Compiled File, Folder DOI

Editorial

  • Sinha, K., Pineau, J., Forde, J., Ke, R. N. & Larochelle, H. [Editorial] NeurIPS 2019 Reproducibility Challenge. Compiled File, Folder DOI