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Molecular contrastive learning with graph attention network (MoCL-GAT) for enhanced molecular representation Dalkıran, Alperen; Rifaioğlu, Ahmet Süreyya; Atalay, Rengül; Acar, Aybar Can; DOĞAN, TUNCA; Atalay, Mehmet Volkan (2026-12-01) Background: Learning the representation of molecules is crucial for drug discovery but is often hindered by the scarcity of labeled experimental data, which limits the performance of supervised machine learning models. Whi...
Evaluating Image Forgery Detection and Propaganda in Manipulated Images of the Russian Trolls Campaign Mohammed, Basem Iqbal; Çetinkaya, Yusuf Mucahit; Elmas, Tuğrulcan (2026-07-01) Generative AI tools have increased the scale and accessibility of deceptive image creation, but the robustness of existing forgery detection methods under emerging editing tools and real-world social media conditions remai...
DTA-GNN: a toolkit for constructing target-specific drug–target affinity datasets and training graph neural networks Özsari, Gökhan; Rifaioğlu, Ahmet Süreyya; Acar, Aybar Can; DOĞAN, TUNCA; Atalay, Mehmet Volkan (2026-06-01) Drug–target affinity (DTA) prediction is a key task in computational drug discovery, yet current research is often compromised by data leakage and non-reproducible preprocessing. We present DTA-GNN, an end-to-end Python to...
Beyond the Black Box: Programmable AI and Explainable Text Analysis for Trustworthy Social Intelligence Trivedi, Anshul; Çetinkaya, Yusuf Mucahit; Cowan, Michael A.; Newson, Martha; Vlahovic, Natko; Davulcu, Hasan (2026-05-01) Life demands safe, reliable, and explainable AI grounded in scientific reasoning and guided by human oversight. We present a neuro-symbolic Programmable AI algorithm that transforms neural outputs into interpretable log...
Subgoal identification with multiple instance learning methods in landmark Partially Observable Markov Decision Process problems Sunel, Saim; Polat, Faruk (2026-05-01)
Intrinsic dimensionality as a model-free measure of class imbalance Eser, Çağrı; Baltaci, Zeynep Sonat; Akbaş, Emre; KALKAN, SİNAN (2026-04-14) Imbalance in classification tasks is commonly quantified by the cardinalities of examples across classes. This, however, disregards the presence of redundant examples and inherent differences in the learning difficulties o...
Firearm brand classification using deep learning on cartridge case images Meral, Edanur; Akyüz, Ahmet Oğuz (2026-02-01) When a firearm is discharged, it leaves characteristic marks on the cartridge case, which are analyzed in forensic ballistics to identify the firearm. Conventional ballistic examination systems rely on high-quality images ...
Guide to Distributed Simulation with HLA Introduction Topçu, Okan; Oğuztüzün, Mehmet Halit S. (2026-02-01)
Efficient utilization of streaming multiprocessors for the implementation of particle filter on graphics processing unit Dülger, Özcan (2026-02-01) The particle filter is a serial Monte Carlo estimation method. It is used in tracking applications in which the system or measurement model is highly nonlinear. The quality of the estimation improves as the number of parti...
Special Issue on High-Performance Computing Conference (BAŞARIM 2024) Karagöz, Pınar; Kaya, Kamer; Manguoğlu, Murat; Şener, Cevat (2026-02-01) This editorial is for the Special Issue on the 8th High-Performance Computing Conference (BAŞARIM 2024), held on May 15–17, 2024, at the Middle East Technical University Culture and Convention Center in Ankara.
Multilayer approximate nullspace methods for saddle point systems Manguoğlu, Murat; Mehrmann, Volker (2026-01-01) We propose a new class of multi-layer iterative schemes for solving sparse linear systems in saddle point structure. The new scheme consists of an iterative preconditioner that is based on the (approximate) nullspace metho...
Federate Implementation: Advanced Topçu, Okan; Oğuztüzün, Mehmet Halit S. (2026-01-01)
Analyzing Privacy Dynamics Within Groups Using Gamified Auctions Aydın, Hüseyin; Ulusoy, Onuralp; Liccardi, Ilaria; Yolum, Pınar (2026-01-01) Online shared content, such as group pictures, often belongs to multiple users having different privacy preferences. Recent technical approaches advocate group-decision mechanisms, including auctions, to decide how best to...
Querying Beyond Keywords: Translating Natural Language to Elasticsearch DSL with Vector Search Support Ozdemir, Aysel Yagmur; Karagöz, Pınar; Toroslu, İsmail Hakkı (2026-01-01) Despite Elasticsearch’s popularity in modern search pipelines, translating natural language queries (NLQs) into its domain-specific language (DSL) remains challenging, especially with the integration of semantic vector sea...
SALDIRAY: Scalable and Adaptive Language Diagnostics for Remediation of Anomalies and Typos Külah, Emre; Çetinkaya, Yusuf Mucahit; Alemdar, Hande (2026-01-01) Natural language processing (NLP) systems working with real-world user data often encounter noisy, informal text, including typos, spelling variations, slang, and homophone substitutions. This noise can cause a severe drop...
Document Reordering for Efficient Dynamic Pruning in Traditional and Learned Sparse Retrieval Yafay, Erman; Altıngövde, İsmail Sengör (2026-01-01) Large scale Web search engines conduct first-stage retrieval using a traditional inverted index, on which they are expected to execute billions of queries on a very tight budget, i.e., less than 200 milliseconds. During qu...
CAPIM: Catalytic activity and site prediction and analysis tool in multimer proteins Özsarı, Gökhan; García-Soriano, Daniela A.; Parate, Shraddha; el Issaoui, Amar; Wittung-Stafshede, Pernilla (2025-11-01) Enzymes play a fundamental role in living organisms by catalyzing vital chemical reactions. While much is known about enzyme function, a substantial portion of the proteome remains uncharacterized. Computational tools have...
DARKIN: a zero-shot benchmark for phosphosite–dark kinase association using protein language models Sunar, Emine Ayşe; Işık, Zeynep; Pekey, Mert; Cinbiş, Ramazan Gökberk; Tastan, Oznur (2025-11-01) Motivation: Protein language models (pLMs) have emerged as powerful tools for capturing the intricate information encoded in protein sequences, facilitating various downstream protein prediction tasks. With numerous pLMs a...
Task assignment strategies for capacitated agents engaged in lifelong pickup and delivery tasks Çilden, Evren; Polat, Faruk (2025-11-01) In this study, we tackled the task assignment problem in the capacity-enhanced version of Multi-Agent Pickup and Delivery (MAPD), a lifelong variant of the classical Multi-Agent Path Finding (MAPF) problem. Capacity-enhanc...
Generalized variational autoencoders for learning disentangled representation Moğultay, Hazal; KALKAN, SİNAN; Vural, Fatos T. Yarman (2025-10-14) The major goal of disentangled representation learning is to form representation space, which independently captures the underlying sources of variation, responsible for generating the data. A pioneering approach is sugges...

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