Tag: featured
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Pure2DopeNet: Multimodal Neural Network-Based Predictive Modeling of Nanoparticle Properties from Pure Compounds
Can Polat, Mustafa Kurban, and Hasan Kurban – IOP’s Machine Learning: Science and Technology
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QuantumShellNet: Ground-State Eigenvalue Prediction of Materials Using Electronic Shell Structures and Fermionic Properties via Convolutions
Can Polat, Hasan Kurban, and Mustafa Kurban – Elsevier’s Computational Materials Science.
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Temporal Graph Neural Networks
Introduction Due to the increasing connectivity in the world, graph data has manifested itself in many contexts, particularly in recent years. Analyzing interactions within graphs makes for an interesting exploration across many applications. While many studies concentrate on static graphs, the changing nature of data requires examining how interactions within a graph change over time.
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PlayoffsNet: Enhancing NBA Playoffs Prediction Through Engineered Features and Explainable Deep Learning
Ganesh Arkanath, Hasan Kurban, Mehmet Dalkilic – ACM KDD 2025 (under-review)
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A simple browser-based Multiplayer Wager Game for Strategy and Risk Analysis
Whether making decisions about personal finances, careers, or daily living, risk analysis and strategy are essential components of decision-making processes for each individual. Individuals can improve results and reduce negative effects by knowing their risk appetite, and strategic planning establishes long-term objectives and practical methods to attain them while taking these risks into account. To
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An Extended de Bruijn Graph for Feature Engineering Over Biological Sequential Data
Mert Onur Cakiroglu, Hasan Kurban, Parichit Sharma, M Oguzhan Kulekci, Elham Khorasani Buxton, Maryam Raeeszadeh-Sarmazdeh, Mehmet M Dalkilic – Machine Learning: Science and Technology
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Enhancing the Electronic Properties of TiO2 Nanoparticles through Carbon Doping: An Integrated DFTB and Computer Vision Approach
Mustafa Kurban, Can Polat, Erchin Serpedin, Hasan Kurban – Elsevier’s Computational Materials Science (Accepted)
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Materials as Graphs
Introduction Graph Neural Networks (GNNs) have emerged as a critical tool for modeling complex relationships and interactions in data, particularly in fields such as social and physical sciences. In this blog, we delve into the applications of GNNs in materials science (MS), an interdisciplinary field that combines elements of physics, chemistry, and engineering to understand
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De Bruijn Graphs
Introduction De Bruijn graphs, named after Dutch mathematician Nicolaas Govert de Bruijn, are invaluable in both computer science and bioinformatics. These graphs efficiently represent overlaps between sequences of symbols, making them essential for sequence analysis applications. While their utility spans various fields, they are predominantly applied in bioinformatics today. We have even recently demonstrated that
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Advolance: Next-Generation Educational Software
In recent years, generative AI technology has become an integral part of our lives, transforming various sectors from content creation to customer service. Now, we are excited to bring this revolutionary technology to programming education with our innovative web software. Our collaborative text editor for learning Python harnesses the power of generative AI to provide
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What Data-Centric AI Can Do For kmeans–a Faster, Robust kmeans-d
Parichit Sharma, Hasan Kurban, Mehmet M. Dalkilic – Proceedings of the 41st International Conference on Machine Learning (ICML), Vienna, Austria, Data Centric Machine Learning Research Workshop (DMLR), 2024 (Accepted)
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Deep Temporal & Structural Embeddings for Unsupervised Anomaly Detection in Dynamic Graphs
Samir Abdaljalil, Hasan Kurban, Rachad Atat, Erchin Serpedin, Khalid Qaraqe – IEEE Transactions on Neural Networks and Learning Systems (under-review)
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Novel De Bruijn Graph Embeddings for Enhanced Time Series Forecasting
Mert Onur Cakiroglu, Hasan Kurban, Elham Khorasani Buxton, Mehmet Dalkilic – Machine Learning (under-review)
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A Reinforcement Learning Approach to Effective Forecasting of Pediatric Hypoglycemia in Diabetes I Patients: an extended de Bruijn Graph
Mert Onur Cakiroglu, Hasan Kurban, Khalid Qaraqe, Lilia Aljihmani, Goran Petrovski, Mehmet Dalkilic – Scientific Reports (under-review)
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Text-To-Energy–Accelerating Quantum Chemistry Calculations through Enhanced Text-to-Vector Encoding and Orbital-Aware Multilayer Perceptron
Can Polat, Hasan Kurban, Mustafa Kurban – Scientific Reports (under-review)
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Geometric-k-means–An Unbounded, Accurate and Energy-Efficient k-means
Parichit Sharma, Hasan Kurban, Marcin Malec, Oguzhan Kulekci, Mehmet Dalkilic – Machine Learning (under-review)
Kurban Intelligence Lab 