arXiv Machine Learning By Jiechen Huang, Hector R. Rodriguez, Dingcheng Yang, Zuochang Ye, Yibo Lin, Wenjian Yu

AttentionCap: Transformer Based Capacitance Matrix Learning Toward Full-Chip Extraction

Read the original on arXiv Machine Learning →

arXiv:2606. 08161v1 Announce Type: new Abstract: As capacitance extraction accuracy of rule-based pattern matching becomes difficult to sustain at advanced nodes, a growing trend emerges to develop deep-learning-based 2D capacitance models.

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arXiv Machine Learning
Jun 4

Breaking the Scale Barrier: One-Shot Knowledge Transfer via Frequency Transform

arXiv:2603. 07523v3 Announce Type: replace Abstract: Transferring knowledge by fine-tuning large-scale pre-trained networks has become a standard paradigm for downstream tasks, yet the knowledge of a pre-trained model is tightly coupled with monolithic architecture, which restricts flexible reuse across models of varying scales.

By Jianlu Shen, Fu Feng, Yucheng Xie, Jiaqi Lv, Xin Geng