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2020 – today
- 2024
[c18]Adhithya Bhaskar
, Victoria Stodden:
Reproscreener: Leveraging LLMs for Assessing Computational Reproducibility of Machine Learning Pipelines. ACM-REP 2024- [c17]Yantong Zheng, Victoria Stodden:
The Idealized Machine Learning Pipeline (IMLP) for Advancing Reproducibility in Machine Learning. ACM-REP 2024 - 2022
- [j11]Manish Parashar, Michael A. Heroux, Victoria Stodden:
Research Reproducibility. Computer 55(8): 16-18 (2022) - 2021
- [c16]Peilun Zhang, Yanjie Jiang, Anjiang Wei, Victoria Stodden, Darko Marinov, August Shi:
Domain-Specific Fixes for Flaky Tests with Wrong Assumptions on Underdetermined Specifications. ICSE 2021: 50-61 - 2020
- [j10]Victoria Stodden:
The data science life cycle: a disciplined approach to advancing data science as a science. Commun. ACM 63(7): 58-66 (2020) - [j9]Dylan Chapp, Victoria Stodden, Michela Taufer:
Building a Vision for Reproducibility in the Cyberinfrastructure Ecosystem: Leveraging Community Efforts. Supercomput. Front. Innov. 7(1): 112-129 (2020) - [c15]Victoria Stodden:
Beyond Open Data: A Model for Linking Digital Artifacts to Enable Reproducibility of Scientific Claims. P-RECS@HPDC 2020: 9-14 - [c14]Wing Lam, Stefan Winter, Angello Astorga, Victoria Stodden, Darko Marinov:
Understanding Reproducibility and Characteristics of Flaky Tests Through Test Reruns in Java Projects. ISSRE 2020: 403-413 - [i7]Kyle Chard, Niall Gaffney, Mihael Hategan, Kacper Kowalik, Bertram Ludäscher, Timothy M. McPhillips, Jarek Nabrzyski, Victoria Stodden, Ian J. Taylor, Thomas Thelen, Matthew J. Turk, Craig Willis:
Toward Enabling Reproducibility for Data-Intensive Research using the Whole Tale Platform. CoRR abs/2005.06087 (2020)
2010 – 2019
- 2019
- [j8]Adam Brinckman, Kyle Chard, Niall Gaffney, Mihael Hategan, Matthew B. Jones, Kacper Kowalik, Sivakumar Kulasekaran, Bertram Ludäscher, Bryce D. Mecum, Jarek Nabrzyski, Victoria Stodden, Ian J. Taylor, Matthew J. Turk, Kandace Turner:
Computing environments for reproducibility: Capturing the "Whole Tale". Future Gener. Comput. Syst. 94: 854-867 (2019) - [c13]Victoria Stodden, Vicki Ferrini, Margaret J. Gabanyi, Kerstin A. Lehnert, John Morton, Helen M. Berman:
Open access to research artifacts: Implementing the next generation data management plan. ASIST 2019: 481-485 - [c12]Kyle Chard, Thomas Thelen, Matthew J. Turk, Craig Willis, Niall Gaffney, Matthew B. Jones, Kacper Kowalik, Bertram Ludäscher, Timothy M. McPhillips, Jarek Nabrzyski, Victoria Stodden, Ian J. Taylor:
Application of BagIt-Serialized Research Object Bundles for Packaging and Re-Execution of Computational Analyses. eScience 2019: 514-521 - [c11]Ewa Deelman, Victoria Stodden, Michela Taufer, Von Welch:
Initial Thoughts on Cybersecurity And Reproducibility. P-RECS@HPDC 2019: 13-15 - [c10]Kyle Chard, Niall Gaffney, Matthew B. Jones, Kacper Kowalik, Bertram Ludäscher, Jarek Nabrzyski, Victoria Stodden, Ian J. Taylor, Matthew J. Turk, Craig Willis:
Implementing Computational Reproducibility in the Whole Tale Environment. P-RECS@HPDC 2019: 17-22 - [c9]Matthew Krafczyk, August Shi, Adhithya Bhaskar, Darko Marinov, Victoria Stodden:
Scientific Tests and Continuous Integration Strategies to Enhance Reproducibility in the Scientific Software Context. P-RECS@HPDC 2019: 23-28 - [c8]Kyle Chard, Niall Gaffney, Mihael Hategan, Kacper Kowalik, Bertram Ludäscher, Timothy M. McPhillips, Jarek Nabrzyski, Victoria Stodden, Ian J. Taylor, Thomas Thelen, Matthew J. Turk, Craig Willis:
Toward Enabling Reproducibility for Data-Intensive Research Using the Whole Tale Platform. PARCO 2019: 766-778 - [i6]Hatef Monajemi, Riccardo Murri, Eric Jonas, Percy Liang, Victoria Stodden, David L. Donoho:
Ambitious Data Science Can Be Painless. CoRR abs/1901.08705 (2019) - 2018
- [j7]Francine Berman, Rob A. Rutenbar, Brent Hailpern, Henrik I. Christensen, Susan B. Davidson, Deborah Estrin, Michael J. Franklin, Margaret Martonosi, Padma Raghavan, Victoria Stodden, Alexander S. Szalay:
Realizing the potential of data science. Commun. ACM 61(4): 67-72 (2018) - [j6]Victoria Stodden, Jennifer Seiler, Zhaokun Ma:
An empirical analysis of journal policy effectiveness for computational reproducibility. Proc. Natl. Acad. Sci. USA 115(11): 2584-2589 (2018) - [c7]Victoria Stodden, Xiaomian Wu, Vanessa V. Sochat:
AIM: An Abstraction for Improving Machine Learning Prediction. DSW 2018: 150-154 - [c6]Victoria Stodden:
Reproducibility in computational and data-enabled science. HPDC 2018: 1 - [i5]Adam Brinckman, Kyle Chard, Niall Gaffney, Mihael Hategan, Matthew B. Jones, Kacper Kowalik, Sivakumar Kulasekaran, Bertram Ludäscher, Bryce D. Mecum, Jarek Nabrzyski, Victoria Stodden, Ian J. Taylor, Matthew J. Turk, Kandace Turner:
Computing Environments for Reproducibility: Capturing the "Whole Tale". CoRR abs/1805.00400 (2018) - 2017
- [i4]Rafael C. Jiménez, Mateusz Kuzak, Monther Alhamdoosh, Michelle Barker, Bérénice Batut, Mikael Borg, Salvador Capella-Gutiérrez, Neil P. Chue Hong, Martin Cook, Manuel Corpas, Madison Flannery, Leyla J. García, Josep Lluis Gelpí, Simon L. Gladman, Carole A. Goble, Montserrat González Ferreiro, Alejandra N. González-Beltrán, Philippa C. Griffin, Björn A. Grüning, Jonas Hagberg, Petr Holub, Rob W. W. Hooft, Jon C. Ison, Daniel S. Katz, Brane Leskosek, Federico López-Gómez, Luis J. Oliveira, David Mellor, Rowland Mosbergen, Nicola J. Mulder, Yasset Pérez-Riverol, Robert Pergl, Horst Pichler, Bernard J. Pope, Ferran Sanz, Maria Victoria Schneider, Victoria Stodden, Radoslaw Suchecki, Radka Svobodová Vareková, Harry-Anton Talvik, Ilian T. Todorov, Andrew E. Treloar, Sonika Tyagi, Maarten van Gompel, Daniel Vaughan, Allegra Via, Xiaochuan Wang, Nathan S. Watson-Haigh, Steve Crouch:
Four simple recommendations to encourage best practices in research software. F1000Research 6: 876- (2017) - 2016
- [c5]Hatef Monajemi, David L. Donoho, Victoria Stodden:
Making massive computational experiments painless. IEEE BigData 2016: 2368-2373 - [i3]Bertram Ludäscher, Kyle Chard, Niall Gaffney, Matthew B. Jones, Jaroslaw Nabrzyski, Victoria Stodden, Matthew J. Turk:
Capturing the "Whole Tale" of Computational Research: Reproducibility in Computing Environments. CoRR abs/1610.09958 (2016) - 2015
- [j5]Victoria Stodden, Sheila Miguez, Jennifer Seiler:
ResearchCompendia.org: Cyberinfrastructure for Reproducibility and Collaboration in Computational Science. Comput. Sci. Eng. 17(1): 12-19 (2015) - 2014
- [i2]Doug James, Nancy Wilkins-Diehr, Victoria Stodden, Dirk Colbry, Carlos Rosales, Mark R. Fahey, Justin Shi, Rafael Ferreira da Silva, Kyo Lee, Ralph Roskies, Laurence Loewe, Susan Lindsey, Rob Kooper, Lorena A. Barba, David H. Bailey, Jonathan M. Borwein, Óscar Corcho, Ewa Deelman, Michael C. Dietze, Benjamin Gilbert, Jan Harkes, Seth Keele, Praveen Kumar, Jong Lee, Erika Linke, Richard Marciano, Luigi Marini, Chris Mattmann, Dave Mattson, Kenton McHenry, Robert T. McLay, Sheila Miguez, Barbara S. Minsker, María S. Pérez-Hernández, Dan Ryan, Mats Rynge, Idafen Santana-Pérez, Mahadev Satyanarayanan, Gloriana St. Clair, Keith Webster, Eivind Hovig, Daniel S. Katz, Sophie Kay, Geir Kjetil Sandve, David Skinner, Gabrielle Allen, John Cazes, Kym Won Cho, Jim Fonseca, Lorraine J. Hwang, Lars Koesterke, Pragnesh Patel, Line Pouchard, Edward Seidel, Isuru Suriarachchi:
Standing Together for Reproducibility in Large-Scale Computing: Report on reproducibility@XSEDE. CoRR abs/1412.5557 (2014) - 2012
- [j4]Victoria Stodden, Randall J. LeVeque, Ian Mitchell:
Reproducible Research for Scientific Computing: Tools and Strategies for Changing the Culture. Comput. Sci. Eng. 14(4): 13-17 (2012) - [c4]Victoria Stodden, Christophe Hurlin, Christophe Pérignon:
RunMyCode.org: A novel dissemination and collaboration platform for executing published computational results. eScience 2012: 1-8 - 2010
- [i1]Victoria Stodden:
Reproducibility of Computational Results: Opening Code and Data. IASSIST 2010
2000 – 2009
- 2009
- [j3]David L. Donoho, Arian Maleki, Inam Ur Rahman, Morteza Shahram, Victoria Stodden:
Reproducible Research in Computational Harmonic Analysis. Comput. Sci. Eng. 11(1): 8-18 (2009) - [j2]Victoria Stodden:
The Legal Framework for Reproducible Scientific Research: Licensing and Copyright. Comput. Sci. Eng. 11(1): 35-40 (2009) - [c3]Victoria Stodden, Patrick Meier:
A global empirical evaluation of new communication technology use and democratic tendency. ICTD 2009: 3-16 - 2006
- [c2]David L. Donoho, Victoria Stodden:
Breakdown Point of Model Selection When the Number of Variables Exceeds the Number of Observations. IJCNN 2006: 1916-1921 - 2005
- [j1]Inam Ur Rahman, Iddo Drori, Victoria Stodden, David L. Donoho, Peter Schröder:
Multiscale Representations for Manifold-Valued Data. Multiscale Model. Simul. 4(4): 1201-1232 (2005) - 2003
- [c1]David L. Donoho, Victoria Stodden:
When Does Non-Negative Matrix Factorization Give a Correct Decomposition into Parts? NIPS 2003: 1141-1148
Coauthor Index
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last updated on 2024-10-07 21:16 CEST by the dblp team
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