40 citations · 50 across the 7 of their papers we have counts for
7 papers
Leverage-Weighted Conformal Prediction
Shreyas Fadnavis
Split conformal prediction provides distribution-free prediction intervals with finite-sample marginal coverage, but produces constant-width intervals that overcover in low-varianc…
PainPoints: A Framework for Language-based Detection of Chronic Pain and Expert-Collaborative Text-Summarization
Shreyas Fadnavis, Amit Dhurandhar, Raquel Norel +6
Chronic pain is a pervasive disorder which is often very disabling and is associated with comorbidities such as depression and anxiety. Neuropathic Pain (NP) is a common sub-type w…
EVAC+: Multi-scale V-net with Deep Feature CRF Layers for Brain Extraction
Jong Sung Park, Shreyas Fadnavis, Eleftherios Garyfallidis
Brain extraction is one of the first steps of pre-processing 3D brain MRI data and a prerequisite for any forthcoming brain imaging analyses. However, it is not a simple segmentati…
NUQ: A Noise Metric for Diffusion MRI via Uncertainty Discrepancy Quantification
Shreyas Fadnavis, Jens Sjölund, Anders Eklund +1
Diffusion MRI (dMRI) is the only non-invasive technique sensitive to tissue micro-architecture, which can, in turn, be used to reconstruct tissue microstructure and white matter pa…
ThetA -- fast and robust clustering via a distance parameter
Eleftherios Garyfallidis, Shreyas Fadnavis, Jong Sung Park +4
Clustering is a fundamental problem in machine learning where distance-based approaches have dominated the field for many decades. This set of problems is often tackled by partitio…
Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning
Shreyas Fadnavis, Joshua Batson, Eleftherios Garyfallidis
Diffusion-weighted magnetic resonance imaging (DWI) is the only noninvasive method for quantifying microstructure and reconstructing white-matter pathways in the living human brain…
Fitting IVIM with Variable Projection and Simplicial Optimization
Shreyas Fadnavis, Hamza Farooq, Maryam Afzali +10
Fitting multi-exponential models to Diffusion MRI (dMRI) data has always been challenging due to various underlying complexities. In this work, we introduce a novel and robust fitt…