14 citations · 19 across the 10 of their papers we have counts for
10 papers
CellxPert: Inference-Time MCMC Steering of a Multi-Omics Single-Cell Foundation Model for In-Silico Perturbation
Andac Demir, Erik W. Anderson, Jeremy L. Jenkins +1
In this work, we introduce CellxPert, a scalable multimodal foundation model that unifies single-cell and spatial multi-omics within a common representation space. CellxPert jointl…
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…
SE(3)-Invariant Multiparameter Persistent Homology for Chiral-Sensitive Molecular Property Prediction
Andac Demir, Francis Prael, Bulent Kiziltan
In this study, we present a novel computational method for generating molecular fingerprints using multiparameter persistent homology (MPPH). This technique holds considerable sign…
Multiparameter Persistent Homology for Molecular Property Prediction
Andac Demir, Bulent Kiziltan
In this study, we present a novel molecular fingerprint generation method based on multiparameter persistent homology. This approach reveals the latent structures and relationships…
Topology-Aware Focal Loss for 3D Image Segmentation
Andac Demir, Elie Massaad, Bulent Kiziltan
The efficacy of segmentation algorithms is frequently compromised by topological errors like overlapping regions, disrupted connections, and voids. To tackle this problem, we intro…
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…