3 papers
cs.CV2026
Not All NVFP4 QAT Recipes Are Equal: How Architecture and Scale Shape Model Quality for Anomaly Segmentation
Zijian Du, Oleg Rybakov
Real-time anomaly segmentation demands both high recall and efficient low-precision inference. We study the three-way interaction of model architecture, model scale, and FP4 quanti…
cond-mat.mtrl-sci2024
VQCrystal: Leveraging Vector Quantization for Discovery of Stable Crystal Structures
ZiJie Qiu, Luozhijie Jin, Zijian Du +5
Discovering functional crystalline materials through computational methods remains a formidable challenge in materials science. Here, we introduce VQCrystal, an innovative deep lea…
cond-mat.mtrl-sci2024
CTGNN: Crystal Transformer Graph Neural Network for Crystal Material Property Prediction
Zijian Du, Luozhijie Jin, Le Shu +4
The combination of deep learning algorithm and materials science has made significant progress in predicting novel materials and understanding various behaviours of materials. Here…