3 citations · 3 across the 9 of their papers we have counts for
6 papers · 1 filter
Classifying Clinical Outcome of Epilepsy Patients with Ictal Chirp Embeddings
Nooshin Bahador, Milad Lankarany
This study presents a pipeline leveraging t-Distributed Stochastic Neighbor Embedding (t-SNE) for interpretable visualizations of chirp features across diverse outcome scenarios. T…
Semi-Supervised Anomaly Detection Pipeline for SOZ Localization Using Ictal-Related Chirp
Nooshin Bahador, Milad Lankarany
This study presents a quantitative framework for evaluating the spatial concordance between clinically defined seizure onset zones (SOZs) and statistically anomalous channels ident…
Stochastic Sparse Sampling: A Framework for Variable-Length Medical Time Series Classification
Xavier Mootoo, Alan A. Díaz-Montiel, Milad Lankarany +1
While the majority of time series classification research has focused on modeling fixed-length sequences, variable-length time series classification (VTSC) remains critical in heal…
Implicit Dynamical Flow Fusion (IDFF) for Generative Modeling
Mohammad R. Rezaei, Milos R. Popovic, Milad Lankarany +1
Conditional Flow Matching (CFM) models can generate high-quality samples from a non-informative prior, but they can be slow, often needing hundreds of network evaluations (NFE). To…
Uncovering the Origins of Instability in Dynamical Systems: How Attention Mechanism Can Help?
Nooshin Bahador, Milad Lankarany
The behavior of the network and its stability are governed by both dynamics of individual nodes as well as their topological interconnections. Attention mechanism as an integral pa…
Deep Direct Discriminative Decoders for High-dimensional Time-series Data Analysis
Mohammad R. Rezaei, Milos R. Popovic, Milad Lankarany +1
The state-space models (SSMs) are widely utilized in the analysis of time-series data. SSMs rely on an explicit definition of the state and observation processes. Characterizing th…