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ORCIDKaustubh R. Patil
Person information
- affiliation: Heinrich Heine University Düsseldorf, Germany
- affiliation: Research Centre Jülich, Germany
- affiliation (former): Massachusetts Institute of Technology, Sloan Neuroeconomics Lab, Cambridge, MA, USA
- affiliation (former): Max Planck Institute for Informatics, Saarbrücken, Germany
- affiliation (PhD 2013): Saarland University, Saarbrücken, Germany
- affiliation: University of Porto, Portugal
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2020 – today
- 2024
[c6]Jinyang Yu
, Sami Hamdan, Leonard Sasse, Abigail Morrison, Kaustubh R. Patil:
Empirical Comparison Between Cross-Validation and Mutation-Validation in Model Selection. IDA (2) 2024: 56-67- [c5]Federico Raimondo, Georgios Antonopoulos, Simon B. Eickhoff, Kaustubh R. Patil:
FastGPR: Divide-and-Conquer Technique in Neuroimaging Data Shortens Training Time and Improves Accuracy. ISBI 2024: 1-4 - [i8]Xiaoliang Luo, Akilles Rechardt, Guangzhi Sun, Kevin K. Nejad, Felipe Yáñez, Bati Yilmaz, Kangjoo Lee, Alexandra O. Cohen, Valentina Borghesani, Anton Pashkov, Daniele Marinazzo, Jonathan Nicholas, Alessandro Salatiello, Ilia Sucholutsky, Pasquale Minervini, Sepehr Razavi, Roberta Rocca, Elkhan Yusifov, Tereza Okalova, Nianlong Gu, Martin Ferianc, Mikail Khona, Kaustubh R. Patil, Pui-Shee Lee, Rui Mata, Nicholas E. Myers, Jennifer K. Bizley, Sebastian Musslick, Isil Poyraz Bilgin, Guiomar Niso, Justin M. Ales, Michael Gaebler, N. Apurva Ratan Murty, Leyla Loued-Khenissi, Anna Behler, Chloe M. Hall, Jessica Dafflon, Sherry Dongqi Bao, Bradley C. Love:
Large language models surpass human experts in predicting neuroscience results. CoRR abs/2403.03230 (2024) - 2023
- [j13]Shammi More, Georgios Antonopoulos, Felix Hoffstaedter, Julian Caspers, Simon B. Eickhoff, Kaustubh R. Patil:
Brain-age prediction: A systematic comparison of machine learning workflows. NeuroImage 270: 119947 (2023) - [j12]Jean-Philippe Kröll, Patrick Friedrich, Xuan Li, Kaustubh R. Patil, Lisa Mochalski, Laura Waite, Xing Qian, Michael W. L. Chee, Juan Helen Zhou, Simon B. Eickhoff, Susanne Weis:
Naturalistic viewing increases individual identifiability based on connectivity within functional brain networks. NeuroImage 273: 120083 (2023) - [j11]Xuan Li, Patrick Friedrich, Kaustubh R. Patil, Simon B. Eickhoff, Susanne Weis:
A topography-based predictive framework for naturalistic viewing fMRI. NeuroImage 277: 120245 (2023) - [j10]Georgios Antonopoulos, Shammi More, Federico Raimondo, Simon B. Eickhoff, Felix Hoffstaedter, Kaustubh R. Patil:
A systematic comparison of VBM pipelines and their application to age prediction. NeuroImage 279: 120292 (2023) - [j9]Nikolay Dagaev, Brett D. Roads, Xiaoliang Luo, Daniel N. Barry, Kaustubh R. Patil, Bradley C. Love:
A too-good-to-be-true prior to reduce shortcut reliance. Pattern Recognit. Lett. 166: 164-171 (2023) - [i7]Sami Hamdan, Shammi More, Leonard Sasse, Vera Komeyer, Kaustubh R. Patil, Federico Raimondo:
Julearn: an easy-to-use library for leakage-free evaluation and inspection of ML models. CoRR abs/2310.12568 (2023) - [i6]Leonard Sasse, Eliana Nicolaisen-Sobesky, Juergen Dukart, Simon B. Eickhoff, Michael Götz, Sami Hamdan, Vera Komeyer, Abhijit Kulkarni, Juha Lahnakoski, Bradley C. Love, Federico Raimondo, Kaustubh R. Patil:
On Leakage in Machine Learning Pipelines. CoRR abs/2311.04179 (2023) - [i5]Jinyang Yu, Sami Hamdan, Leonard Sasse, Abigail Morrison, Kaustubh R. Patil:
Empirical Comparison between Cross-Validation and Mutation-Validation in Model Selection. CoRR abs/2311.14079 (2023) - 2022
- [j8]María Goñi, Simon B. Eickhoff, Mehran Sahandi Far, Kaustubh R. Patil, Juergen Dukart:
Smartphone-Based Digital Biomarkers for Parkinson's Disease in a Remotely-Administered Setting. IEEE Access 10: 28361-28384 (2022) - [j7]Vinita Periwal, Stefan Bassler, Sergej Andrejev, Natalia Gabrielli, Kaustubh Raosaheb Patil, Athanasios Typas, Kiran Raosaheb Patil:
Bioactivity assessment of natural compounds using machine learning models trained on target similarity between drugs. PLoS Comput. Biol. 18(4) (2022) - [i4]Kaustubh R. Patil, Simon B. Eickhoff, Robert Langner:
Predictive Data Calibration for Linear Correlation Significance Testing. CoRR abs/2208.07081 (2022) - [i3]Sami Hamdan, Bradley C. Love, Georg G. von Polier, Susanne Weis, Holger Schwender, Simon B. Eickhoff, Kaustubh R. Patil:
Confound-leakage: Confound Removal in Machine Learning Leads to Leakage. CoRR abs/2210.09232 (2022) - 2021
- [j6]Patrick Friedrich, Stephanie J. Forkel, Céline Amiez, Joshua H. Balsters, Olivier Coulon, Lingzhong Fan, Alexandros Goulas, Fadila Hadj-Bouziane, Erin E. Hecht, Katja Heuer, Tianzi Jiang, Robert D. Latzman, Xiaojin Liu, KepKee Loh, Kaustubh R. Patil, Alizée Lopez-Persem, Emmanuel Procyk, Jérôme Sallet, Roberto Toro, Sam Vickery, Susanne Weis, Charles R. E. Wilson, Ting Xu, Valerio Zerbi, Simon B. Eickhoff, Daniel S. Margulies, Rogier B. Mars, Michel Thiebaut de Schotten:
Imaging evolution of the primate brain: the next frontier? NeuroImage 228: 117685 (2021) - [j5]Xiaojin Liu, Simon B. Eickhoff, Svenja Caspers, Jianxiao Wu, Sarah Genon, Felix Hoffstaedter, Rogier B. Mars, Iris E. Sommer, Claudia R. Eickhoff, Ji Chen, Renaud Jardri, Kathrin Reetz, Imis Dogan, André Aleman, Lydia Kogler, Oliver Gruber, Julian Caspers, Christian Mathys, Kaustubh R. Patil:
Functional parcellation of human and macaque striatum reveals human-specific connectivity in the dorsal caudate. NeuroImage 235: 118006 (2021) - [i2]Nikolay Dagaev, Brett D. Roads, Xiaoliang Luo, Daniel N. Barry, Kaustubh R. Patil, Bradley C. Love:
A Too-Good-to-be-True Prior to Reduce Shortcut Reliance. CoRR abs/2102.06406 (2021) - 2020
- [c4]Jean-Philippe Kröll, Simon B. Eickhoff, Felix Hoffstaedter, Kaustubh R. Patil:
Evolving complex yet interpretable representations: application to Alzheimer's diagnosis and prognosis. CEC 2020: 1-8 - [c3]Shammi More, Simon B. Eickhoff, Julian Caspers, Kaustubh R. Patil:
Confound Removal and Normalization in Practice: A Neuroimaging Based Sex Prediction Case Study. ECML/PKDD (5) 2020: 3-18
2010 – 2019
- 2019
- [c2]Laura Muzzarelli, Susanne Weis, Simon B. Eickhoff, Kaustubh R. Patil:
Rank Selection in Non-negative Matrix Factorization: systematic comparison and a new MAD metric. IJCNN 2019: 1-8 - 2018
- [j4]Guillem Collell, Drazen Prelec, Kaustubh R. Patil:
A simple plug-in bagging ensemble based on threshold-moving for classifying binary and multiclass imbalanced data. Neurocomputing 275: 330-340 (2018) - [j3]Deepthi P. Varikuti, Sarah Genon, Aristeidis Sotiras, Holger Schwender, Felix Hoffstaedter, Kaustubh R. Patil, Christiane Jockwitz, Svenja Caspers, Susanne Moebus, Katrin Amunts, Christos Davatzikos, Simon B. Eickhoff:
Evaluation of non-negative matrix factorization of grey matter in age prediction. NeuroImage 173: 394-410 (2018) - 2017
- [j2]Gagan Joshi, Sheeba Arnold Anteraper, Kaustubh R. Patil, Meha Semwal, Rachel L. Goldin, Stephannie L. Furtak, Xiaoqian J. Chai, Zeynep M. Saygin, John D. E. Gabrieli, Joseph Biederman, Susan L. Whitfield-Gabrieli:
Integration and Segregation of Default Mode Network Resting-State Functional Connectivity in Transition-Age Males with High-Functioning Autism Spectrum Disorder: A Proof-of-Concept Study. Brain Connect. 7(9): 558-573 (2017) - 2016
- [i1]Guillem Collell, Drazen Prelec, Kaustubh R. Patil:
Reviving Threshold-Moving: a Simple Plug-in Bagging Ensemble for Binary and Multiclass Imbalanced Data. CoRR abs/1606.08698 (2016) - 2014
- [c1]Kaustubh R. Patil, Xiaojin Zhu, Lukasz Kopec, Bradley C. Love:
Optimal Teaching for Limited-Capacity Human Learners. NIPS 2014: 2465-2473 - 2013
- [b1]Kaustubh R. Patil:
Genome signature based sequence comparison for taxonomic assignment and tree inference. Saarland University, 2013
2000 – 2009
- 2008
- [j1]Kaustubh R. Patil, Abhijit Kulkarni:
Kernel-enabled methods for subspace regression and efficient control. Int. J. Model. Identif. Control. 5(2): 136-145 (2008)
Coauthor Index
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