1 citations · 1 across the 6 of their papers we have counts for
6 papers
The AI Neuroscientist: An Interactive Agentic Interface for Neuroimaging Analysis
Aakash Patel, Panos Ketonis, Shreya Saxena +2
Analyzing neuroimaging data requires specialized coding and statistical expertise, which limits accessibility for researchers without computational backgrounds. We present the AI N…
scShapeBench: Discovering geometry from high dimensional scRNAseq data
Andrew J Steindl, João Felipe Rocha, Brian Tshilengi Di Bassinga +13
High-dimensional point cloud data arise across many scientific domains, especially single-cell biology. The shapes or topologies of these datasets determine the types of informatio…
Linearized Optimal Transport for Analysis of High-Dimensional Point-Cloud and Single-Cell Data
Tianxiang Wang, Yingtong Ke, Dhananjay Bhaskar +2
Single-cell technologies generate high-dimensional point clouds of cells, enabling detailed characterization of complex patient states and treatment responses. Yet each patient is…
Looking through the mind's eye via multimodal encoder-decoder networks
Arman Afrasiyabi, Erica Busch, Rahul Singh +4
In this work, we explore the decoding of mental imagery from subjects using their fMRI measurements. In order to achieve this decoding, we first created a mapping between a subject…
Latent Representation Learning for Multimodal Brain Activity Translation
Arman Afrasiyabi, Dhananjay Bhaskar, Erica L. Busch +5
Neuroscience employs diverse neuroimaging techniques, each offering distinct insights into brain activity, from electrophysiological recordings such as EEG, which have high tempora…
ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images
Chen Liu, Ke Xu, Liangbo L. Shen +8
Advances in medical imaging technologies have enabled the collection of longitudinal images, which involve repeated scanning of the same patients over time, to monitor disease prog…