暂无分享,去创建一个
Annibale Panichella | Mathijs de Weerdt | Przemyslaw Pawelczak | Stjepan Picek | Hayley Hung | Cynthia C. S. Liem | Jesse H. Krijthe | Marco Loog | Jan van Gemert | Frans Oliehoek | Gosia Migut | Burak Yildiz | J. V. Gemert | M. Loog | S. Picek | P. Pawełczak | J. Krijthe | M. D. Weerdt | Annibale Panichella | Hayley Hung | Frans Oliehoek | Burak Yildiz | Gosia Migut
[1] Kyle Gorman,et al. We Need to Talk about Standard Splits , 2019, ACL.
[2] Konrad Hinsen,et al. ReScience C: A Journal for Reproducible Replications in Computational Science , 2018, RRPR.
[3] Edward Raff,et al. A Step Toward Quantifying Independently Reproducible Machine Learning Research , 2019, NeurIPS.
[4] Andrew McCallum,et al. Open Scholarship and Peer Review: a Time for Experimentation , 2013 .
[5] André Freitas,et al. The Diagrammatic AI Language (DIAL): Version 0.1 , 2018, ArXiv.
[6] Zachary C. Lipton,et al. Troubling Trends in Machine Learning Scholarship , 2018, ACM Queue.
[7] Benjamin Recht,et al. Do ImageNet Classifiers Generalize to ImageNet? , 2019, ICML.
[8] Chris Dyer,et al. On the State of the Art of Evaluation in Neural Language Models , 2017, ICLR.
[9] Senthil Mani,et al. DLPaper2Code: Auto-generation of Code from Deep Learning Research Papers , 2017, AAAI.
[10] Dietmar Jannach,et al. Are we really making much progress? A worrying analysis of recent neural recommendation approaches , 2019, RecSys.
[11] D. Sculley,et al. Winner's Curse? On Pace, Progress, and Empirical Rigor , 2018, ICLR.
[12] David Coeurjolly,et al. Code replicability in computer graphics , 2020, ACM Trans. Graph..
[13] Marco Loog,et al. Black Magic in Deep Learning: How Human Skill Impacts Network Training , 2020, BMVC.
[14] Jimmy J. Lin,et al. The Neural Hype and Comparisons Against Weak Baselines , 2019, SIGIR Forum.
[15] Nick McKeown,et al. Learning Networking by Reproducing Research Results , 2017, CCRV.
[16] Bertrand Kerautret,et al. An Overview of Platforms for Reproducible Research and Augmented Publications , 2018, RRPR.
[17] Philip Bachman,et al. Deep Reinforcement Learning that Matters , 2017, AAAI.
[18] Larry Rudolph,et al. Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO , 2020, ArXiv.
[19] Michela Paganini,et al. dagger: A Python Framework for Reproducible Machine Learning Experiment Orchestration , 2020, ArXiv.
[20] C. Drummond. Replicability is not Reproducibility:Nor is it Good Science , 2009 .
[21] Ser-Nam Lim,et al. A Metric Learning Reality Check , 2020, ECCV.
[22] Jasper Snoek,et al. Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling , 2018, ICLR.
[23] Mario Lucic,et al. Are GANs Created Equal? A Large-Scale Study , 2017, NeurIPS.
[24] M. Hutson. Artificial intelligence faces reproducibility crisis. , 2018, Science.
[25] Pascal Monasse,et al. IPOL: A new journal for fully reproducible research; analysis of four years development , 2015, NTMS.