Contents

Under review

See https://github.com/ReScience/submissions/issues

Volume 7 (2021)

Issue 2 (ML Reproducibility Challenge 2020)

  1. Replication in ML Reproducibility Challenge 2020 (Python) | 10.5281/zenodo.4835602 | PDF | Code | Review | BibTeX
    Verma, R., Wagemans, J.J.O., Dahal, P., and Elfrink, A. 2021. [Re] Explaining Groups of Points in Low-Dimensional Representations. ReScience C 7, 2, #24.

  2. Replication in ML Reproducibility Challenge 2020 (Python) | 10.5281/zenodo.4833219 | PDF | Code | Data | Review | BibTeX
    Albanis, G., Zioulis, N., Chatzitofis, A., Dimou, A., Zarpalas, D., and Daras, P. 2021. [Re] On end-to-end 6DoF object pose estimation and robustness to object scale. ReScience C 7, 2, #2.

  3. Replication in ML Reproducibility Challenge 2020 (python) | 10.5281/zenodo.4833389 | PDF | Code | Review | BibTeX
    Arvind, M. and Mama, M. 2021. [Re] Neural Networks Fail to Learn Periodic Functions and How to Fix It. ReScience C 7, 2, #3.

  4. Replication in ML Reproducibility Challenge 2020 (python) | 10.5281/zenodo.4833547 | PDF | Code | Review | BibTeX
    Teule, T., Reints, N., Gerges, C.A., and Baanders, P. 2021. [Re] Deep Fair Clustering for Visual Learning. ReScience C 7, 2, #4.

  5. Replication in ML Reproducibility Challenge 2020 (Python) | 10.5281/zenodo.4833681 | PDF | Code | Review | BibTeX
    Garg, P., Singhal, L., and Sardana, A. 2021. [Re] Training Binary Neural Networks using the Bayesian Learning Rule. ReScience C 7, 2, #5.

  6. Replication in ML Reproducibility Challenge 2020 (Python 3) | 10.5281/zenodo.4834146 | PDF | Code | Data | Review | BibTeX
    Habacker, R., Harrison, A., Parisot, M., and Snijders, A. 2021. [Re] Reproducing Learning to Deceive With Attention-Based Explanations. ReScience C 7, 2, #6.

  7. Replication in ML Reproducibility Challenge 2020 (English) | 10.5281/zenodo.4834242 | PDF | Code | Review | BibTeX
    Holdijk, L., Boon, M., Henckens, S., and Jong, L. de. 2021. [Re] Parameterized Explainer for Graph Neural Network. ReScience C 7, 2, #7.

  8. Replication in ML Reproducibility Challenge 2020 (Python) | 10.5281/zenodo.4834352 | PDF | Code | Review | BibTeX
    Kim, S.S.Y., Zhang, S., Meister, N., and Russakovsky, O. 2021. [Re] Don’t Judge an Object by Its Context: Learning to Overcome Contextual Bias. ReScience C 7, 2, #8.

  9. Replication in ML Reproducibility Challenge 2020 (Python) | 10.5281/zenodo.4834442 | PDF | Code | Review | BibTeX
    Li, C., Tu, R., and Zhang, H. 2021. [Re] Reimplementation of FixMatch and Investigation on Noisy (Pseudo) Labels and Confirmation Errors of FixMatch. ReScience C 7, 2, #9.

  10. Replication in ML Reproducibility Challenge 2020 (Python) | 10.5281/zenodo.4834516 | PDF | Code | Review | BibTeX
    Liiv, T., Lennelöv, E., and Norén, A. 2021. [Re] A Reproduction of Ensemble Distribution Distillation. ReScience C 7, 2, #10.

  11. Replication in ML Reproducibility Challenge 2020 (Python) | 10.5281/zenodo.4834610 | PDF | Code | Review | BibTeX
    Stephen, K. and Menon, V. 2021. [Re] Learning Memory Guided Normality for Anomaly Detection. ReScience C 7, 2, #11.

  12. Replication in ML Reproducibility Challenge 2020 (Python) | 10.5281/zenodo.4834672 | PDF | Code | Review | BibTeX
    Menteş, S., Kınlı, F., Özcan, B., and Kıraç, F. 2021. [Re] Spatial-Adaptive Network for Single Image Denoising. ReScience C 7, 2, #12.

  13. Replication in ML Reproducibility Challenge 2020 (Python) | 10.5281/zenodo.4834744 | PDF | Code | Review | BibTeX
    Mizrahi, D., Yüksel, O.K., and Kyzy, A.M. 2021. [Re] Can gradient clipping mitigate label noise? ReScience C 7, 2, #13.

  14. Replication in ML Reproducibility Challenge 2020 (python) | 10.5281/zenodo.4834856 | PDF | Code | Review | BibTeX
    Kireev, K., Mohtashami, A., and Pajouheshgar, E. 2021. [Re] Warm-Starting Neural Network Training. ReScience C 7, 2, #14.

  15. Replication in ML Reproducibility Challenge 2020 (Python) | 10.5281/zenodo.4834942 | PDF | Code | Review | BibTeX
    P, J.J. and Sardana, A. 2021. [Re] Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings. ReScience C 7, 2, #15.

  16. Replication in ML Reproducibility Challenge 2020 (Python) | 10.5281/zenodo.4835056 | PDF | Code | Review | BibTeX
    Reijnaers, D.J.W., Pavert, D.B. van de, Scheuer, G., and Huang, L. 2021. [Re] Explaining Groups of Points in Low-Dimensional Representations. ReScience C 7, 2, #16.

  17. Replication in ML Reproducibility Challenge 2020 (Python 3) | 10.5281/zenodo.4839595 | PDF | Code | Review | BibTeX
    Deprez, H.L. gezegd, Rijsdijk, G., Rooij, B. de, and Zwerink, W. 2021. [Re] Reproducing ’Identifying through flows for recovering latent representations.’ ReScience C 7, 2, #17.

  18. Replication in ML Reproducibility Challenge 2020 (Python) | 10.5281/zenodo.4835278 | PDF | Code | Review | BibTeX
    Balsells Rodas, C., Canal Anton, O., and Taschin, F. 2021. [Re] Hamiltonian Generative Networks. ReScience C 7, 2, #18.

  19. Replication in ML Reproducibility Challenge 2020 (python) | 10.5281/zenodo.4835356 | PDF | Code | Data | BibTeX
    Schneider, M. and Körner, M. 2021. [Re] Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention. ReScience C 7, 2, #19.

  20. Replication in ML Reproducibility Challenge 2020 (Python) | 10.5281/zenodo.4835431 | PDF | Code | Review | BibTeX
    Sheverdin, A., Knijff, A., Corten, N., and Lange, G. 2021. [Re] Reproducibility report of "Interpretable Complex-Valued Neural Networks for Privacy Protection". ReScience C 7, 2, #20.

  21. Replication in ML Reproducibility Challenge 2020 (Python) | 10.5281/zenodo.4835564 | PDF | Code | Review | BibTeX
    Sundar, V. and Dwaraknath, R.V. 2021. [Re] Rigging the Lottery: Making All Tickets Winners. ReScience C 7, 2, #21.

  22. Replication in ML Reproducibility Challenge 2020 (Python) | 10.5281/zenodo.4835592 | PDF | Code | Review | BibTeX
    Bouwman, P., Li, Y., Weerd, R. van der, and Verhoef, F. 2021. [Re] Reproducibility study - Does enforcing diversity in hidden states of LSTM-Attention models improve transparency? ReScience C 7, 2, #22.

  23. Replication in ML Reproducibility Challenge 2020 (python) | 10.5281/zenodo.4835600 | PDF | Code | Review | BibTeX
    Verhoeven, I., Chen, X., Hu, Q., and Holubar, M. 2021. [Re] Replication Study of ’Generative causal explanations of black-box classifiers.’ ReScience C 7, 2, #23.

  24. Editorial | 10.5281/zenodo.4833117 | PDF | BibTeX
    Sinha, K., Dodge, J., Luccioni, S., Forde, J.Z., Stojnic, R., and Pineau, J. 2021. ML Reproducibility Challenge 2020. ReScience C 7, 2, #1.

Issue 1

  1. Replication in Ecology (R) | 10.5281/zenodo.5006005 | PDF | Code | Data | BibTeX
    Boersch-Supan, P.H. 2021. [Re] Modeling Insect Phenology Using Ordinal Regression and Continuation Ratio Models. ReScience C 7, 1, #5.

  2. Replication in Algorithmics (C++) | 10.5281/zenodo.4836230 | PDF | Code | Review | BibTeX
    Lécuyer, F., Danisch, M., and Tabourier, L. 2021. [Re] Speedup Graph Processing by Graph Ordering. ReScience C 7, 1, #3.

  3. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.4655870 | PDF | Code | Review | BibTeX
    Boraud, T. and Strock, A. 2021. [Re] A Neurodynamical Model for Working Memory. ReScience C 7, 1, #1.

  4. Replication in Game Theory (Python 3) | 10.5281/zenodo.4646680 | PDF | Code | Review | BibTeX
    Geoffroy, F. 2021. [Re] Assortative matching and search. ReScience C 7, 1, #2.

Volume 6 (2020)

Issue 3

  1. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.4461767 | PDF | Code | Review | BibTeX
    Torre-Ortiz, C. de la and Nioche, A. 2021. [Re] Neural Network Model of Memory Retrieval. ReScience C 6, 3, #8.

  2. Replication in Reinforcement Learning (python) | 10.5281/zenodo.4242943 | PDF | Code | Review | BibTeX
    Brückner, L. and Nioche, A. 2020. [Re] Faster Teaching via POMDP Planning. ReScience C 6, 3, #7.

  3. Replication in Computational Neuroscience (Julia) | 10.5281/zenodo.4139359 | PDF | Code | Review | BibTeX
    Davies, I. and Eglen, S. 2020. [Re] The principal components of natural images. ReScience C 6, 3, #6.

  4. Replication in Ecology (julia) | 10.5281/zenodo.4022518 | PDF | Code | Review | BibTeX
    Dansereau, G., Banville, F., Basque, E., MacDonald, A., and Poisot, T. 2020. [Re] Chaos in a Three-Species Food Chain. ReScience C 6, 3, #5.

  5. Replication in Neuroscience (Matlab) | 10.5281/zenodo.4022361 | PDF | Code | Review | BibTeX
    Hentschke, H. 2020. [Re] Hippocampal Phase-Amplitude Coupling unearthed again. ReScience C 6, 3, #3.

  6. Replication in Computer Science | 10.5281/zenodo.3885793 | PDF | Code | Review | BibTeX
    Mahmoudian, S. 2020. [Re] Measures for investigating the contextual modulation of information transmission. ReScience C 6, 3, #2.

  7. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.3842360 | PDF | Code | Review | BibTeX
    Upshall, M. and Shifman, A.R. 2020. [Re] Mathematical analysis of depolarization block mediated by slow inactivation of fast sodium channels in midbrain dopamine neurons. ReScience C 6, 3, #1.

Issue 2 (NeurIPS 2019 Reproducibility Challenge)

  1. Editorial | 10.5281/zenodo.3818627 | PDF | BibTeX
    Sinha, K., Pineau, J., Forde, J., Ke, R.N., and Larochelle, H. 2020. NeurIPS 2019 Reproducibility Challenge. ReScience C 6, 2, #11.

  2. Replication in NeurIPS 2019 Reproducibility Challenge (Python) | 10.5281/zenodo.3818607 | PDF | Code | Review | BibTeX
    Nayak, N., Raj, V., and Kalyani, S. 2020. [Re] A comprehensive study on binary optimizer and its applicability. ReScience C 6, 2, #9.

  3. Replication in NeurIPS 2019 Reproducibility Challenge (Python) | 10.5281/zenodo.3818609 | PDF | Code | Review | BibTeX
    Matosevic, A., Hein, E., and Nuzzo, F. 2020. [Re] Generative Modeling by Estimating Gradients of the Data Distribution. ReScience C 6, 2, #8.

  4. Replication in NeurIPS 2019 Reproducibility Challenge (Python) | 10.5281/zenodo.3818613 | PDF | Code | Review | BibTeX
    Liljefors, F., Sorkhei, M., and Broomé, S. 2020. [Re] Unsupervised Scalable Representation Learning for Multivariate Time Series. ReScience C 6, 2, #6.

  5. Replication in NeurIPS 2019 Reproducibility Challenge (Python) | 10.5281/zenodo.3818617 | PDF | Code | Review | BibTeX
    Kviman, O., Nilsson, L., and Larsson, M. 2020. [Re] Tensor Monte Carlo: Particle Methods for the GPU Era. ReScience C 6, 2, #5.

  6. Replication in NeurIPS 2019 Reproducibility Challenge (Python) | 10.5281/zenodo.3818621 | PDF | Code | Review | BibTeX
    Garg, A. and Kagi, S.S. 2020. [Re] Hamiltonian Neural Networks. ReScience C 6, 2, #3.

  7. Replication in NeurIPS 2019 Reproducibility Challenge (Python) | 10.5281/zenodo.3818623 | PDF | Code | BibTeX
    Ferles, A., Nöu, A., and Valavanis, L. 2020. [Re] Zero-Shot Knowledge Transfer via Adversarial Belief Matching. ReScience C 6, 2, #2.

  8. Replication in NeurIPS 2019 Reproducibility Challenge (Python) | 10.5281/zenodo.3818611 | PDF | Code | Review | BibTeX
    Liu, Y., Xu, J., and Pan, Y. 2020. [Re] When to Trust Your Model: Model-Based Policy Optimization. ReScience C 6, 2, #7.

  9. Replication in NeurIPS 2019 Reproducibility Challenge (Python) | 10.5281/zenodo.3818625 | PDF | Code | Review | BibTeX
    Alacchi, G., Lam, G., and Perreault-Lafleur, C. 2020. [Re] Unsupervised Representation Learning in Atari. ReScience C 6, 2, #1.

  10. Replication in NeurIPS 2019 Reproducibility Challenge (Python) | 10.5281/zenodo.3818619 | PDF | Code | Review | BibTeX
    Gohil, V., Narayanan, S.D., and Jain, A. 2020. [Re] One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers. ReScience C 6, 2, #4.

  11. Replication in NeurIPS 2019 Reproducibility Challenge (Python) | 10.5281/zenodo.3818605 | PDF | Code | Review | BibTeX
    Singh, A. and Bay, A. 2020. [Re] Improved Calibration and Predictive Uncertainty for Deep Neural Networks. ReScience C 6, 2, #10.

Issue 1 (Ten Years Reproducibility Challenge)

  1. Reproduction in Earth sciences (R) | 10.5281/zenodo.4617894 | PDF | Code | Data | Review | BibTeX
    Bond-Lamberty, B. 2021. [Re] Drivers of evapotranspiration from boreal wildfires. ReScience C 6, 1, #21.

  2. Replication in Computational Neuroscience (C) | 10.5281/zenodo.4543356 | PDF | Code | Review | BibTeX
    Leblois, A. 2021. [Re] Reproduction of the normal and pathological dynamics in the basal ganglia-thalamo-cortical network. ReScience C 6, 1, #19.

  3. Replication in Discrete Mathematics (C) | 10.5281/zenodo.4242972 | PDF | Code | Data | Review | BibTeX
    Enge, A. 2020. [Re] Volume computation for polytopes: Vingt ans après. ReScience C 6, 1, #17.

  4. Reproduction in Biology (SAS) | 10.5281/zenodo.4290512 | PDF | Code | Review | BibTeX
    Barnett, A. 2020. [Rp] Estimating trends and seasonality in coronary heart disease. ReScience C 6, 1, #18.

  5. Reproduction in Pattern Recognition (Java) | 10.5281/zenodo.4091742 | PDF | Code | Data | Review | BibTeX
    Weinman, J. 2020. [Rp] Reproducing "Typographical Features for Scene Text Recognition". ReScience C 6, 1, #.

  6. Reproduction in Ecology (C, R) | 10.5281/zenodo.4081202 | PDF | Code | Review | BibTeX
    Boettiger, C. 2020. [Rp] Fluctuation domains in adaptive evolution. ReScience C 6, 1, #15.

  7. Reproduction in Computational Neuroscience (Hoc) | 10.5281/zenodo.3972130 | PDF | Code | Review | BibTeX
    Davison, A.P. 2020. [Rp] Dendrodendritic inhibition and simulated odor responses in a detailed olfactory bulb network model. ReScience C 6, 1, #14.

  8. Reproduction in Aquatic Science (Pascal) | 10.5281/zenodo.3996198 | PDF | Data | Review | BibTeX
    Silberbauer, M. 2020. Re ReScience challenge: Geographical Trends in the Water Chemistry of Wetlands in the South-Western Cape Province, South Africas. ReScience C 6, 1, #13.

  9. Reproduction in Astronomy (fortran) | 10.5281/zenodo.3956058 | PDF | Code | Data | Review | BibTeX
    Roukema, B.F. 2020. [¬Rp] Reproducibility of ’Poincaré dodecahedral space parameter estimates.’ ReScience C 6, 1, #11.

  10. Reproduction in Genetics (R) | 10.5281/zenodo.3959516 | PDF | Code | Data | BibTeX
    Broman, K.W. 2020. [Rp] Reproducibility report: Identifying essential genes by mutagenesis. ReScience C 6, 1, #12.

  11. Reproduction in Physics (Fortran) | 10.5281/zenodo.3922195 | PDF | Code | Review | BibTeX
    Maggi, S. 2020. [Rp] Reproduction of Step width enhancement in a pulse-driven Josephson junction. ReScience C 6, 1, #10.

  12. Reproduction in Computational Mechanics (C++) | 10.5281/zenodo.3901241 | PDF | Code | Review | BibTeX
    Pantalé, O. 2020. [Rp] Parallelization of an object-oriented FEM dynamics code. ReScience C 6, 1, #8.

  13. Reproduction in Fault Tolerance (C) | 10.5281/zenodo.3886739 | PDF | Code | Review | BibTeX
    Courtès, L. 2020. [Re] Storage Tradeoffs in a Collaborative Backup Service for Mobile Devices. ReScience C 6, 1, #6.

  14. Reproduction in Fluid dynamics (Fortran77) | 10.5281/zenodo.3889694 | PDF | Code | Review | BibTeX
    Hinsen, K. 2020. [¬Rp] Stokes drag on conglomerates of spheres. ReScience C 6, 1, #7.

  15. Reproduction in Computer Science (Applesoft Basic) | 10.5281/zenodo.3886628 | PDF | Code | BibTeX
    Rougier, N.P. 2020. [Rp] LOUPE. ReScience C 6, 1, #3.

  16. Reproduction in Biophysics (Python) | 10.5281/zenodo.3886447 | PDF | Code | Review | BibTeX
    Hinsen, K. 2020. [Rp] Structural flexibility in proteins - impact of the crystal environment. ReScience C 6, 1, #5.

  17. Reproduction in Biophysics (Mathematica) | 10.5281/zenodo.3886412 | PDF | Code | Review | BibTeX
    Robert, C.H. 2020. [Rp] Reproducibility report: Estimating friction coefficients of mixed globular/chain molecules, such as protein/DNA complexes. [Biophys J 69, 840-848 (1995)]. ReScience C 6, 1, #4.

  18. Reproduction in Analytical Chemistry (FORTRAN77) | 10.5281/zenodo.3904595 | PDF | Code | Review | BibTeX
    Delsuc, M.-A. 2020. [Rp] Gifa V.4: A complete package for NMR data set processing. ReScience C 6, 1, #9.

  19. Reproduction in Parallel Programming (OCaml) | 10.5281/zenodo.4041602 | PDF | Code | Review | BibTeX
    Di Cosmo, R. and Danelutto, M. 2020. [Rp] Reproducing and replicating the OCamlP3l experiment. ReScience C 6, 1, #2.

  20. Reproduction in Chemical Physics (Fortran) | 10.5281/zenodo.3630224 | PDF | Code | Review | BibTeX
    McBane, G.C. 2020. [Rp] Reproduction of interaction second virial coefficient calculation for H_2–CO interactions [J. Chem. Phys. vol. 112, 4417 (2000)]. ReScience C 6, 1, #1.

Volume 5 (2019)

Issue 3

  1. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.3538217 | PDF | Code | Review | BibTeX
    Larisch, R. 2019. [Re] Connectivity reflects coding a model of voltage-based STDP with homeostasis. ReScience C 5, 3, #2.

  2. Letter in Machine Learning (c++) | 10.5281/zenodo.3528175 | PDF | Code | Review | BibTeX
    Sukhoy, V. and Stoytchev, A. 2019. Eliminating the Variability of Cross-Validation Results with LIBLINEAR due to Randomization and Parallelization. ReScience C 5, 3, #1.

  3. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.3545905 | PDF | Code | Review | BibTeX
    Bock, P. and Alexandre, F. 2019. [Re] The Wisconsin Card Sorting Test: Theoretical analysis and modeling in a neuronal network. ReScience C 5, 3, #3.

Issue 2 (ICLR Reproducibility Challenge 2019)

  1. Editorial | 10.5281/zenodo.3158244 | PDF | Review | BibTeX
    Pineau, J., Sinha, K., Fried, G., Ke, R.N., and Larochelle, H. 2019. ICLR Reproducibility Challenge 2019. ReScience C 5, 2, #5.

  2. Replication in Machine Learning (Python) | 10.5281/zenodo.3160540 | PDF | Code | Review | BibTeX
    Devos, A., Chatel, S., and Grossglauser, M. 2019. [Re] Meta-learning with differentiable closed-form solvers. ReScience C 5, 2, #1.

  3. Replication in Machine Learning (Python) | 10.5281/zenodo.3161734 | PDF | Code | Review | BibTeX
    Fuente, A.D. la and Aduviri, R. 2019. [Re] Variational Sparse Coding. ReScience C 5, 2, #2.

  4. Replication in Machine Learning (Python) | 10.5281/zenodo.3162890 | PDF | Code | Review | BibTeX
    Bardi, F., von Baussnern, S., and Gjiriti, E. 2019. [Re] Learning Neural PDE Solvers with Convergence Guarantees ICLR Reproducibility Challenge 2019. ReScience C 5, 2, #3.

  5. Replication in Machine Learning (python) | 10.5281/zenodo.3162114 | PDF | Code | Review | BibTeX
    Didolkar, A. 2019. [Re] h-detach: Modifying the LSTM gradient towards better optimization. ReScience C 5, 2, #4.

Issue 1

  1. Replication in Ecology (Python) | 10.5281/zenodo.3234524 | PDF | Code | Review | BibTeX
    Etherington, T.R. and Lieske, D.J. 2019. [Re] Resampling methods for evaluating classification accuracy of wildlife habitat models. ReScience C 5, 1, #4.

  2. Editorial | 10.5281/zenodo.3069619 | PDF | BibTeX
    Hinsen, K. and Rougier, N.P. 2019. ReScience (R)evolution. ReScience C 5, 1, #3.

  3. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.2611252 | PDF | Code | Review | BibTeX
    Tennøe, S., Hodne, K., Haug, T.M., Weltzien, F.-A., Einevoll, G.T., and Halnes, G. 2019. [Re] Fast-Activating Voltage- and Calcium-Dependent Potassium (BK) Conductance Promotes Bursting in Pituitary Cells: A Dynamic Clamp Study. ReScience 5, 1, #2.

  4. Replication in Computational Ecology (Julia) | 10.5281/zenodo.2598793 | PDF | Code | Review | BibTeX
    Caron, D., Lessard, V., Wu, Q., and Poisot, T. 2019. [Re] Insect natural enemies as regulating factors. ReScience 5, 1, #1.

Volume 4 (2018)

Issue 1

  1. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.1327348 | PDF | Code | Review | BibTeX
    Hathway, P. and Goodman, D.F.M. 2018. [Re] Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike Trains. ReScience 4, 1, #6.

  2. Replication in Computational Ecology (Julia) | 10.5281/zenodo.1402676 | PDF | Code | Review | BibTeX
    Poisot, T. 2018. [Re] On the coexistence of specialists and generalists. ReScience 4, 1, #7.

  3. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.1289889 | PDF | Code | Review | BibTeX
    Bavard, S. and Théro, H. 2018. [Re] Adaptive properties of differential learning rates for positive and negative outcomes. ReScience 4, 1, #5.

  4. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.1246659 | PDF | Code | Review | BibTeX
    Cazé, R., Stimberg, M., and Girard, B. 2018. [Re] Non-additive coupling enables propagation of synchronous spiking activity in purely random networks. ReScience 4, 1, #1.

  5. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.1244116 | PDF | Code | Review | BibTeX
    Shimoura, R.O., Kamij, N.L., Pena, R.F.O., et al. 2018. [Re] The cell-type specific cortical microcircuit: relating structure and activity in a full-scale spiking network model. ReScience 4, 1, #2.

  6. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.1241004 | PDF | Code | Review | BibTeX
    Senden, M., Schuecker, J., Hahne, J., Diesmann, M., and Goebel, R. 2018. [Re] A neural model of the saccade generator in the reticular formation. ReScience 4, 1, #3.

  7. Replication in Computational Biology (Python) | 10.5281/zenodo.1254629 | PDF | Code | Review | BibTeX
    Mondeel, T.D.G.A., Ogundipe, V., and Westerhoff, H.V. 2018. [Re] Predicting metabolic biomarkers of human inborn errors of metabolism. ReScience 4, 1, #4.

Volume 3 (2017)

Issue 1

  1. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.1003214 | PDF | Code | Review | BibTeX
    Detorakis, G. 2017. [Re] A Generalized Linear Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviors. ReScience 3, 1, #7.

  2. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.890901 | PDF | Code | Review | BibTeX
    Diem, A.K. 2017. [Re] A bidirectional model for communication in the neurovascular unit. ReScience 3, 1, #9.

  3. Replication in Computational Evolution (R) | 10.5281/zenodo.890884 | PDF | Code | Review | BibTeX
    Stojić, H. 2017. [Re] How learning can guide evolution. ReScience 3, 1, #8.

  4. Replication in Game Theory (Python) | 10.5281/zenodo.847732 | PDF | Code | Review | BibTeX
    Stollmeier, F. 2017. [Re] A simple rule for the evolution of cooperation on graphs and social networks. ReScience 3, 1, #5.

  5. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.854616 | PDF | Code | Review | BibTeX
    Metzner, C. 2017. [Re] Modeling GABA Alterations in Schizophrenia: A Link Between Impaired Inhibition and Gamma and Beta Auditory Entrainment. ReScience 3, 1, #6.

  6. Replication in Computer Graphics (Python) | 10.5281/zenodo.802285 | PDF | Code | Data | Review | BibTeX
    Rougier, N.P. 2017. [Re] Weighted Voronoi Stippling. ReScience 3, 1, #4.

  7. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.583814 | PDF | Code | Review | BibTeX
    Rostami, V., Ito, J., Denker, M., and Grün, S. 2017. [Re] Spike Synchronization and Rate Modulation Differentially Involved in Motor Cortical Function. ReScience 3, 1, #3.

  8. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.495237 | PDF | Code | Review | BibTeX
    Henriques, R.N., Rokem, A., Garyfallidis, E., St-Jean, S., Peterson, E.T., and Correia, M.M. 2017. [Re] Optimization of a free water elimination two-compartment model for diffusion tensor imaging. ReScience 3, 1, #2.

  9. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.254145 | PDF | Code | Review | BibTeX
    Shifman, A. 2017. [Re] Ionic Current Model of a Hypoglossal Motoneuron. ReScience 3, 1, #1.

Volume 2 (2016)

Issue 1

  1. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.200334 | PDF | Code | Review | BibTeX
    Masson, E.L. and Alexandre, F. 2016. [Re] How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks. ReScience 2, 1, #7.

  2. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.159545 | PDF | Code | Review | BibTeX
    Vitay, J. 2016. [Re] Robust timing and motor patterns by taming chaos in recurrent neural networks. ReScience 2, 1, #5.

  3. Replication in Computational Neurosience (Python) | 10.5281/zenodo.161526 | PDF | Code | Review | BibTeX
    Maksimov, A., Albada, S.J. van, and Diesmann, M. 2016. [Re] Cellular and network mechanisms of slow oscillatory activity (<1 Hz) and wave propagations in a cortical network model. ReScience 2, 1, #6.

  4. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.61697 | PDF | Code | Review | BibTeX
    Detorakis, G. 2016. [Re] Multiple dynamical modes of thalamic relay neurons: rhythmic bursting and intermittent phase-locking. ReScience 2, 1, #4.

  5. Replication in Computational Ecology (R) | 10.5281/zenodo.50213 | PDF | Code | Review | BibTeX
    Petchey, O., Plebani, M., and Pennekamp, F. 2016. [Re] Chaos in a long-term experiment with a plankton community. ReScience 2, 1, #3.

  6. Replication in Computational Ecology (R) | 10.5281/zenodo.47146 | PDF | Code | Review | BibTeX
    Stachelek, J. 2016. [Re] Least-cost modelling on irregular landscape graphs. ReScience 2, 1, #2.

  7. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.45852 | PDF | Code | Review | BibTeX
    Viejo, G., Girard, B., and Khamassi, M. 2016. [Re] Speed/accuracy trade-off between the habitual and the goal-directed process. ReScience 2, 1, #1.

Volume 1 (2015)

Issue 1

  1. Replication in Computational Neuroscience (Python) | 10.5281/zenodo.27944 | PDF | Code | Review | BibTeX
    Topalidou, M. and Rougier, N.P. 2015. [Re] Interaction between cognitive and motor cortico-basal ganglia loops during decision making: a computational study. ReScience 1, 1, #1.