Search Results for author: Erdem Varol

Found 9 papers, 2 papers with code

Subtyping brain diseases from imaging data

no code implementations16 Feb 2022 Junhao Wen, Erdem Varol, Zhijian Yang, Gyujoon Hwang, Dominique Dwyer, Anahita Fathi Kazerooni, Paris Alexandros Lalousis, Christos Davatzikos

The imaging community has increasingly adopted machine learning (ML) methods to provide individualized imaging signatures related to disease diagnosis, prognosis, and response to treatment.

Three-dimensional spike localization and improved motion correction for Neuropixels recordings

no code implementations NeurIPS 2021 Julien Boussard, Erdem Varol, Hyun Dong Lee, Nishchal Dethe, Liam Paninski

Neuropixels (NP) probes are dense linear multi-electrode arrays that have rapidly become essential tools for studying the electrophysiology of large neural populations.

Denoising Spike Sorting

MAGIC: Multi-scale Heterogeneity Analysis and Clustering for Brain Diseases

1 code implementation1 Jul 2020 Junhao Wen, Erdem Varol, Ganesh Chand, Aristeidis Sotiras, Christos Davatzikos

There is a growing amount of clinical, anatomical and functional evidence for the heterogeneous presentation of neuropsychiatric and neurodegenerative diseases such as schizophrenia and Alzheimers Disease (AD).

Clustering Hippocampus

Sinkhorn EM: An Expectation-Maximization algorithm based on entropic optimal transport

no code implementations30 Jun 2020 Gonzalo Mena, Amin Nejatbakhsh, Erdem Varol, Jonathan Niles-Weed

We study Sinkhorn EM (sEM), a variant of the expectation maximization (EM) algorithm for mixtures based on entropic optimal transport.

Temporal Wasserstein non-negative matrix factorization for non-rigid motion segmentation and spatiotemporal deconvolution

no code implementations7 Dec 2019 Erdem Varol, Amin Nejatbakhsh, Conor McGrory

Motion segmentation for natural images commonly relies on dense optic flow to yield point trajectories which can be grouped into clusters through various means including spectral clustering or minimum cost multicuts.

Clustering Motion Segmentation +2

Wasserstein total variation filtering

no code implementations23 Oct 2019 Erdem Varol, Amin Nejatbakhsh

In this paper, we expand upon the theory of trend filtering by introducing the use of the Wasserstein metric as a means to control the amount of spatiotemporal variation in filtered time series data.

Time Series Time Series Analysis

Sinkhorn Permutation Variational Marginal Inference

no code implementations pproximateinference AABI Symposium 2019 Gonzalo Mena, Erdem Varol, Amin Nejatbakhsh, Eviatar Yemini, Liam Paninski

This problem is known to quickly become intractable as the size of the permutation increases, since its involves the computation of the permanent of a matrix, a #P-hard problem.

Robust approximate linear regression without correspondence

no code implementations1 Jun 2019 Amin Nejatbakhsh, Erdem Varol

Previous theoretical analysis of the problem has been done in a setting where the responses are a complete permutation of the regressed covariates.

regression

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