| Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty N Breznau, EM Rinke, A Wuttke, M Adem, J Adriaans, ... Proceedings of the National Academy of Sciences 119 (44), 2022 | 148 | 2022 |
| How cross-validation can go wrong and what to do about it M Neunhoeffer, S Sternberg Political Analysis 27 (1), 101-106, 2019 | 62 | 2019 |
| Really Useful Synthetic Data--A Framework to Evaluate the Quality of Differentially Private Synthetic Data C Arnold, M Neunhoeffer arXiv preprint arXiv:2004.07740, 2020 | 48 | 2020 |
| The role of hyperparameters in machine learning models and how to tune them C Arnold, L Biedebach, A Küpfer, M Neunhoeffer Political Science Research and Methods, 2024 | 40 | 2024 |
| Private Post-GAN Boosting M Neunhoeffer, ZS Wu, C Dwork International Conference on Learning Representations, 2021 | 39 | 2021 |
| Forecasting Elections in Multiparty Systems: A Bayesian Approach Combining Polls and Fundamentals LF Stoetzer, M Neunhoeffer, T Gschwend, S Munzert, S Sternberg Political Analysis 27 (2), 255-262, 2019 | 33 | 2019 |
| Zweitstimme. org. Ein strukturell-dynamisches Vorhersagemodell für Bundestagswahlen S Munzert, L Stötzer, T Gschwend, M Neunhoeffer, S Sternberg PVS Politische Vierteljahresschrift 58 (3), 418-441, 2017 | 17 | 2017 |
| The Crowdsourced Replication Initiative: Investigating Immigration and Social Policy Preferences. Executive Report. N Breznau, EM Rinke, A Wuttke, M Adem, J Adriaans, ... | 9 | 2019 |
| The Zweitstimme model: A dynamic forecast of the 2021 German federal election T Gschwend, K Müller, S Munzert, M Neunhoeffer, LF Stoetzer PS: Political Science & Politics 55 (1), 85-90, 2022 | 6 | 2022 |
| How many replicators does it take to achieve reliability? Investigating researcher variability in a crowdsourced replication N Breznau, EM Rinke, A Wuttke, HHV Nguyen, M Adem, J Adriaans, ... SocArXiv, 2021 | 6 | 2021 |
| An Approach to Predicting the District Vote Shares in German Federal Elections M Neunhoeffer, T Gschwend, S Munzert, LF Stoetzer POLITISCHE VIERTELJAHRESSCHRIFT, 2020 | 5* | 2020 |
| Continual Release of Differentially Private Synthetic Data from Longitudinal Data Collections M Bun, M Gaboardi, M Neunhoeffer, W Zhang Proceedings of the ACM on Management of Data 2 (2), 1-26, 2024 | 4* | 2024 |
| How to Improve the Substantive Interpretation of Regression Results when the Dependent Variable is logged O Rittmann, M Neunhoeffer, T Gschwend Political Science Research and Methods, 1-9, 2023 | 3 | 2023 |
| Generating Synthetic Data is Complicated: Know Your Data and Know Your Generator J Latner, M Neunhoeffer, J Drechsler International Conference on Privacy in Statistical Databases, 115-128, 2024 | 1 | 2024 |
| Rallying around the leader in times of crises: The opposing effects of perceived threat and anxiety R Lehrer, O Bahnsen, K Müller, M Neunhoeffer, T Gschwend, S Juhl European Journal of Political Research, 2024 | 1 | 2024 |
| How to improve the substantive interpretation of regression results when the dependent variable is logged–ERRATUM O Rittmann, M Neunhoeffer, T Gschwend Political Science Research and Methods, 1-1, 2023 | | 2023 |
| Generative adversarial nets for social scientists M Neunhoeffer | | 2023 |
| Book Review: Diana C Mutz, In-Your-Face Politics: The Consequences of Uncivil Media M Neunhoeffer Political Studies Review 16 (1), NP76-NP76, 2018 | | 2018 |
| On the Formal Privacy Guarantees of Synthetic Data M Neunhoeffer, J Latner, J Drechsler | | |
| Bootstrap-based, General-purpose Statistical Inference from Differential Private Releases M Neunhoeffer, D Sheldon, A Smith | | |
Thomas GschwendUniversity of MannheimVerified email at uni-mannheim.de