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Peer-reviewed research on artificial intelligence, extended reality, and behavioral analytics.
Corpus-driven research analysis of the ISO GQL standard: 309 papers in the graph-query-languages category, +235.7% YoY (141 papers in the last 12 months), four research threads (theory, NL2GQL, engines, GQL-as-primitive), the author community, and the field's sharpest gap — only 8 reviews against 309 papers.
Can GNNs predict arithmetic properties of modular forms? We construct trace-index graphs from Fourier coefficient data — 1000 nodes per modular form, connected by sequential, primality, and kNN edges — and show ChebConv achieves R²=0.625 for L-function zero prediction on 46,347 newforms from the LMFDB. Spectral filters outperform GCN by +14.61pp in macro F1 on rank classification.
Empirical evaluation of layer-aware quantization for deploying large language models on consumer hardware. Covers 3-bit KV cache compression (TQ3_0), hybrid GPTQ-INT4+FP8 quantization, and identifying 48K tokens as the practical context sweet spot for coding tasks on 12GB GPUs.
Comprehensive scientific paper on browser-based Virtual Reality Exposure Therapy (VRET). A rigorous academic examination of how WebXR technologies can democratize mental health interventions, covering theoretical foundations, clinical protocols, meta-analytic evidence, and technical implementation.
PhD Dissertation — Investigating adaptive assistance systems and user experience optimization in virtual reality shopping environments. Examines how intelligent assistance systems can adapt to user behavior and context, optimizing the balance between guidance and autonomy.
Master Thesis — Recommendations via Graph Neural Networks. A comprehensive guide covering message passing frameworks, key architectures (GCN, GAT, GraphSAGE, MPNN), applications in recommendation systems, implementation frameworks, and current research directions.
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Ein umfassender Überblick über Graph Neural Networks, der Architekturen, Trainingstechniken und Anwendungen in der Analyse graphstrukturierter Daten abdeckt
A comprehensive overview of Graph Neural Networks covering architectures, training techniques, and applications in graph-structured data analysis
Ein umfassender Leitfaden zum Aufbau produktionsreifer agentischer Command-Line-Interfaces, abgeleitet von Mustern modernster Implementierungen wie Claude Code