Kaustubh R. Patil

Orcid: 0000-0002-0289-5480

Affiliations:
  • 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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Online presence:

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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

Large language models surpass human experts in predicting neuroscience results.
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
A systematic comparison of VBM pipelines and their application to age prediction.
NeuroImage, October, 2023

A topography-based predictive framework for naturalistic viewing fMRI.
NeuroImage, August, 2023

Naturalistic viewing increases individual identifiability based on connectivity within functional brain networks.
NeuroImage, June, 2023

Brain-age prediction: A systematic comparison of machine learning workflows.
NeuroImage, April, 2023

A too-good-to-be-true prior to reduce shortcut reliance.
Pattern Recognit. Lett., February, 2023

On Leakage in Machine Learning Pipelines.
CoRR, 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

Confound-leakage: Confound Removal in Machine Learning Leads to Leakage.
CoRR, 2022

Predictive Data Calibration for Linear Correlation Significance Testing.
CoRR, 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

Imaging evolution of the primate brain: the next frontier?
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
Evaluation of non-negative matrix factorization of grey matter in age prediction.
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
Optimal Teaching for Limited-Capacity Human Learners.
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
Kernel-enabled methods for subspace regression and efficient control.
Int. J. Model. Identif. Control., 2008


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