We design Big Data infrastructures to enable efficient, open and reproducible neuroinformatics.
New paper: The impact of FreeSurfer versions on structural neuroimaging analyses of Parkinson's disease
New paper: Why experimental variation in neuroimaging should be embraced
New pre-print: Training Compute-Optimal Vision Transformers for Brain Encoding
New pre-print: An Analysis of Performance Bottlenecks in MRI Pre-Processing
New pre-print: Open-source tools and platforms to investigate analytical variability in neuroimaging
New pre-print: Hierarchical storage management in user space for neuroimaging applications
New pre-print: Scaling up ridge regression for brain encoding in a massive individual fMRI dataset
New pre-print: The Impact of Hardware Variability on Applications Packaged with Docker and Guix: a Case Study in Neuroimaging
New pre-print: Predicting Parkinson's disease trajectory using clinical and functional MRI features: a reproduction and replication study
New pre-print: Classification of Anomalies in Telecommunication Network KPI Time Series
New pre-print: Numerical Uncertainty of Convolutional Neural Networks Inference for Structural Brain MRI Analysis
New pre-print: A numerical variability approach to results stability tests and its application to neuroimaging
New pre-print: Longitudinal brain structure changes in Parkinson's disease: a replication study
New pre-print: Numerical Stability of DeepGOPlus Inference
New pre-print: Dynamic Ensemble Size Adjustment for Memory Constrained Mondrian Forest
New pre-print: Sea: A lightweight data-placement library for Big Data scientific computing
New pre-print: NeuroCI: Continuous Integration of Neuroimaging Results Across Software Pipelines and Datasets
New pre-print: Mondrian Forest for Data Stream Classification Under Memory Constraints
🚨 Open position: postdoctoral fellow (now filled)
New pre-print: PyTracer: Automatically profiling numerical instabilities in Python
New pre-print: The benefits of prefetching for large-scale cloud-based neuroimaging analysis workflows
New pre-print: A Recommender System for Scientific Datasets and Analysis Pipelines
New pre-print: Accurate simulation of operating system updates in neuroimaging using Monte-Carlo arithmetic
New pre-print: Reducing numerical precision preserves classification accuracy in Mondrian Forests
New pre-print: Modeling the Linux page cache for accurate simulation of data-intensive applications
New pre-print: Data Augmentation Through Monte Carlo Arithmetic Leads to More Generalizable Classification in Connectomics
New pre-print: An Analysis of Security Vulnerabilities in Container Images for Scientific Data Analysis
New pre-print: Numerical Instabilities in Analytical Pipelines Lead to Large and Meaningful Variability in Brain Networks.
New pre-print: A benchmark of data stream classification for human activity recognition on connected objects.
New pre-print: Can we Estimate Truck Accident Risk from Telemetric Data using Machine Learning?
New pre-print: File-based localization of numerical perturbations in data analysis pipelines.
New pre-print: Performance benefits of Intel® Optane™ DC persistent memory for the parallel processing of large neuroimaging data.