Kaustubh R. Patil
Orcid: 0000-0002-0289-5480Affiliations:
- Heinrich Heine University Düsseldorf, Germany
- Research Centre Jülich, Germany
- Massachusetts Institute of Technology, Sloan Neuroeconomics Lab, Cambridge, MA, USA (former)
- Max Planck Institute for Informatics, Saarbrücken, Germany (former)
- Saarland University, Saarbrücken, Germany (PhD 2013)
- University of Porto, Portugal
According to our database1,
Kaustubh R. Patil
authored at least 28 papers
between 2008 and 2024.
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Book In proceedings Article PhD thesis Dataset OtherLinks
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Bibliography
2024
The impact of MRI image quality on statistical and predictive analysis on voxel based morphology.
CoRR, 2024
Impact of Leakage on Data Harmonization in Machine Learning Pipelines in Class Imbalance Across Sites.
CoRR, 2024
CoRR, 2024
FastGPR: Divide-and-Conquer Technique in Neuroimaging Data Shortens Training Time and Improves Accuracy.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024
Empirical Comparison Between Cross-Validation and Mutation-Validation in Model Selection.
Proceedings of the Advances in Intelligent Data Analysis XXII, 2024
2023
NeuroImage, October, 2023
NeuroImage, August, 2023
Naturalistic viewing increases individual identifiability based on connectivity within functional brain networks.
NeuroImage, June, 2023
NeuroImage, April, 2023
Pattern Recognit. Lett., February, 2023
Julearn: an easy-to-use library for leakage-free evaluation and inspection of ML models.
CoRR, 2023
2022
Bioactivity assessment of natural compounds using machine learning models trained on target similarity between drugs.
PLoS Comput. Biol., 2022
Smartphone-Based Digital Biomarkers for Parkinson's Disease in a Remotely-Administered Setting.
IEEE Access, 2022
2021
Functional parcellation of human and macaque striatum reveals human-specific connectivity in the dorsal caudate.
NeuroImage, 2021
2020
Confound Removal and Normalization in Practice: A Neuroimaging Based Sex Prediction Case Study.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 2020
Evolving complex yet interpretable representations: application to Alzheimer's diagnosis and prognosis.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020
2019
Rank Selection in Non-negative Matrix Factorization: systematic comparison and a new MAD metric.
Proceedings of the International Joint Conference on Neural Networks, 2019
2018
NeuroImage, 2018
A simple plug-in bagging ensemble based on threshold-moving for classifying binary and multiclass imbalanced data.
Neurocomputing, 2018
2017
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., 2017
2016
Reviving Threshold-Moving: a Simple Plug-in Bagging Ensemble for Binary and Multiclass Imbalanced Data.
CoRR, 2016
2014
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
2013
Genome signature based sequence comparison for taxonomic assignment and tree inference.
PhD thesis, 2013
2008
Int. J. Model. Identif. Control., 2008