A GNN-ODE surrogate forecasts reactor thermal-hydraulics under partial observability, achieving low MAE on held-out transients, fast inference, and recovery of a physical Reynolds-number exponent after fine-tuning on limited experimental data.
Brin et al., ‘Comparing ChatGPT and GPT -4 performance in USMLE soft skill assessments’, Sci Rep, vol
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QQMR applies Q-learning with priority queuing and fuzzy C-means clustering to select multipath routes in IoMT body area networks, raising packet delivery while cutting delay, overhead, and energy use.
Marangoni-driven flows explain heterogeneous Piezo1 distribution in epithelial cells and higher activity in cancer cells through membrane interactions and driving forces.
Lightweight U-Net outperforms DDPM on T2w-to-MRI-SFF translation (r=0.975 vs 0.962, MAE=0.014 vs 0.019) with 208x faster inference on 230k paired images from NAKO.
Hybrid classical adiabatic annealing yields marginal improvements on limited MaxCut instances but offers no substantial practical benefit over existing techniques for Ising machines.
IncepDeHazeGAN is a GAN with Inception blocks and multi-layer feature fusion that claims state-of-the-art single-image dehazing performance on satellite datasets.
Endoshare is a publicly released surgeon-friendly tool for merging, standardizing, and de-identifying endoscopic videos, validated with high usability scores from internal and external clinician surveys plus performance tests across hardware.
GPT-4o and Claude 3.5 Sonnet reach 73.7-74% accuracy on gastroenterology questions; VLMs gain nothing from images and lose accuracy with LLM-generated captions.
PyCC.id packages a hypothesis-driven method using identifiable ODE skeletons for equation discovery from data, supporting multiple paradigms like neural networks and sparse regression.
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Vision-Language and Large Language Model Performance in Gastroenterology: GPT, Claude, Llama, Phi, Mistral, Gemma, and Quantized Models
GPT-4o and Claude 3.5 Sonnet reach 73.7-74% accuracy on gastroenterology questions; VLMs gain nothing from images and lose accuracy with LLM-generated captions.