Copertina

Fast Cell Library Characterization for Design Technology Co-Optimization Based on Graph Neural Networks

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ma, Tianliang, Fan, Guangxi, Deng, Zhihui, Sun, Xuguang, Low, Kainlu, Shao, Leilai
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Late Breaking Results: Fast System Technology Co-Optimization Framework for Emerging Technology Based on Graph Neural Networks
di: Ma, Tianliang, et al.
Pubblicazione: (2024)

AgenticTCAD: A LLM-based Multi-Agent Framework for Automated TCAD Code Generation and Device Optimization
di: Fan, Guangxi, et al.
Pubblicazione: (2025)

Revolutionizing TCAD Simulations with Universal Device Encoding and Graph Attention Networks
di: Fan, Guangxi, et al.
Pubblicazione: (2023)

Chiplet Placement Order Exploration Based on Learning to Rank with Graph Representation
di: Deng, Zhihui, et al.
Pubblicazione: (2024)

Hierarchical Decoupling Capacitor Optimization for Power Distribution Network of 2.5D ICs with Co-Analysis of Frequency and Time Domains Based on Deep Reinforcement Learning
di: Duan, Yuanyuan, et al.
Pubblicazione: (2024)

RLPlanner: Reinforcement Learning based Floorplanning for Chiplets with Fast Thermal Analysis
di: Duan, Yuanyuan, et al.
Pubblicazione: (2023)

Towards Fair Graph Neural Networks via Graph Counterfactual without Sensitive Attributes
di: Wang, Xuemin, et al.
Pubblicazione: (2024)

Backdoor Attack on Vertical Federated Graph Neural Network Learning
di: Yang, Jirui, et al.
Pubblicazione: (2024)

LCQNN: Linear Combination of Quantum Neural Networks
di: Yao, Hongshun, et al.
Pubblicazione: (2025)

Fast Graph Condensation with Structure-based Neural Tangent Kernel
di: Wang, Lin, et al.
Pubblicazione: (2023)

Fast and Reliable $N-k$ Contingency Screening with Input-Convex Neural Networks
di: Christianson, Nicolas, et al.
Pubblicazione: (2024)

Safety, Feasibility and Prognostic Analysis of Surgical Treatment for High‐Complexity Renal Tumours (RENAL Score ≥ 10): A Summary of Experience With Robotic Technology Applications
di: Lijing Xu, et al.
Pubblicazione: (2026)

SAU: A Dual-Branch Network to Enhance Long-Tailed Recognition via Generative Models
di: Li, Guangxi, et al.
Pubblicazione: (2024)

Tensor Networks Meet Neural Networks: A Survey and Future Perspectives
di: Wang, Maolin, et al.
Pubblicazione: (2023)

RATLIP: Generative Adversarial CLIP Text-to-Image Synthesis Based on Recurrent Affine Transformations
di: Lin, Chengde, et al.
Pubblicazione: (2024)

Fast Graph Neural Network for Image Classification
di: Gharasuie, Mustafa Mohammadi, et al.
Pubblicazione: (2025)

Global, Regional, and National Burden of Chronic Kidney Disease Attributable to High Body Mass Index (BMI) among Individuals Aged 20-54 Years from 1990 to 2021: An Analysis of the Global Burden of Disease Study
di: Chen, Yu, et al.
Pubblicazione: (2025)

Time Varying Efficiency and Asymmetric Extreme Risk Spillover Effects: Evidence From the Chinese and US Stock Markets
di: Wenhao Xie, et al.
Pubblicazione: (2026)

Text2VP: Generative AI for Visual Programming and Parametric Modeling
di: Feng, Guangxi, et al.
Pubblicazione: (2024)

Graph in Graph Neural Network
di: Wang, Jiongshu, et al.
Pubblicazione: (2024)

Advancements in Recommender Systems: A Comprehensive Analysis Based on Data, Algorithms, and Evaluation
di: Ma, Xin, et al.
Pubblicazione: (2024)

KirchhoffNet: A Scalable Ultra Fast Analog Neural Network
di: Gao, Zhengqi, et al.
Pubblicazione: (2023)

Enhanced Pre-training of Graph Neural Networks for Million-Scale Heterogeneous Graphs
di: Sun, Shengyin, et al.
Pubblicazione: (2025)

Graph Neural Networks Automated Design and Deployment on Device-Edge Co-Inference Systems
di: Zhou, Ao, et al.
Pubblicazione: (2024)

MASPOB: Bandit-Based Prompt Optimization for Multi-Agent Systems with Graph Neural Networks
di: Hong, Zhi, et al.
Pubblicazione: (2026)

Differentiable Cluster Graph Neural Network
di: Dong, Yanfei, et al.
Pubblicazione: (2024)

Evolutionary Optimization of Physics-Informed Neural Networks: Advancing Generalizability by the Baldwin Effect
di: Wong, Jian Cheng, et al.
Pubblicazione: (2023)

Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs
di: Yue, Zichao, et al.
Pubblicazione: (2025)

Learning Granularity Representation for Temporal Knowledge Graph Completion
di: Zhang, Jinchuan, et al.
Pubblicazione: (2024)

Co-Evolution-Based Metal-Binding Residue Prediction with Graph Neural Networks
di: Rastegari, Sayedmohammadreza, et al.
Pubblicazione: (2025)

MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training
di: Peng, Hongwu, et al.
Pubblicazione: (2023)

Decidability of Graph Neural Networks via Logical Characterizations
di: Benedikt, Michael, et al.
Pubblicazione: (2024)

Hardware-Aware Quantum Kernel Design Based on Graph Neural Networks
di: Meng, Fanxu, et al.
Pubblicazione: (2025)

JEDI-linear: Fast and Efficient Graph Neural Networks for Jet Tagging on FPGAs
di: Que, Zhiqiang, et al.
Pubblicazione: (2025)

Neural Dueling Bandits: Preference-Based Optimization with Human Feedback
di: Verma, Arun, et al.
Pubblicazione: (2024)

A Scalable Neural Network for DSIC Affine Maximizer Auction Design
di: Duan, Zhijian, et al.
Pubblicazione: (2023)

A Unified Framework for Combinatorial Optimization Based on Graph Neural Networks
di: Jin, Yaochu, et al.
Pubblicazione: (2024)

Graph Neural Networks for Fast Contingency Analysis of Power Systems
di: Nakiganda, Agnes M., et al.
Pubblicazione: (2023)

Inference-friendly Graph Compression for Graph Neural Networks
di: Fan, Yangxin, et al.
Pubblicazione: (2025)

FastPFRec: A Fast Personalized Federated Recommendation with Secure Sharing
di: Yan, Zhenxing, et al.
Pubblicazione: (2026)