14 citations · 17 across the 5 of their papers we have counts for
6 papers
sc-OTGM: Single-Cell Perturbation Modeling by Solving Optimal Mass Transport on the Manifold of Gaussian Mixtures
Andac Demir, Elizaveta Solovyeva, James Boylan +6
Influenced by breakthroughs in LLMs, single-cell foundation models are emerging. While these models show successful performance in cell type clustering, phenotype classification, a…
EEG-NeXt: A Modernized ConvNet for The Classification of Cognitive Activity from EEG
Andac Demir, Iya Khalil, Bulent Kiziltan
One of the main challenges in electroencephalogram (EEG) based brain-computer interface (BCI) systems is learning the subject/session invariant features to classify cognitive activ…
ToDD: Topological Compound Fingerprinting in Computer-Aided Drug Discovery
Andac Demir, Baris Coskunuzer, Ignacio Segovia-Dominguez +3
In computer-aided drug discovery (CADD), virtual screening (VS) is used for identifying the drug candidates that are most likely to bind to a molecular target in a large library of…
EEG-GNN: Graph Neural Networks for Classification of Electroencephalogram (EEG) Signals
Andac Demir, Toshiaki Koike-Akino, Ye Wang +2
Convolutional neural networks (CNN) have been frequently used to extract subject-invariant features from electroencephalogram (EEG) for classification tasks. This approach holds th…
EEG-based Texture Roughness Classification in Active Tactile Exploration with Invariant Representation Learning Networks
Ozan Ozdenizci, Safaa Eldeeb, Andac Demir +2
During daily activities, humans use their hands to grasp surrounding objects and perceive sensory information which are also employed for perceptual and motor goals. Multiple corti…
AutoBayes: Automated Bayesian Graph Exploration for Nuisance-Robust Inference
Andac Demir, Toshiaki Koike-Akino, Ye Wang +1
Learning data representations that capture task-related features, but are invariant to nuisance variations remains a key challenge in machine learning. We introduce an automated Ba…