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3rd MLCAD 2021: Raleigh, NC, USA
- 3rd ACM/IEEE Workshop on Machine Learning for CAD, MLCAD 2021, Raleigh, NC, USA, August 30 - Sept. 3, 2021. IEEE 2021, ISBN 978-1-6654-3166-8
- Daniela Sanchez Lopera, Lorenzo Servadei, Gamze Naz Kiprit, Souvik Hazra, Robert Wille, Wolfgang Ecker:
A Survey of Graph Neural Networks for Electronic Design Automation. 1-6 - Shuyuan Yu, Yibo Liu, Sheldon X.-D. Tan:
Approximate Divider Design Based on Counting-Based Stochastic Computing Division. 1-6 - Luis Francisco, Paul D. Franzon, W. Rhett Davis:
Fast and Accurate PPA Modeling with Transfer Learning. 1-6 - Jie Xiong, Alan Yang, Maxim Raginsky, Elyse Rosenbaum:
Neural Networks for Transient Modeling of Circuits : Invited Paper. 1-7 - Yaguang Li, Yishuang Lin, Meghna Madhusudan, Arvind K. Sharma, Sachin S. Sapatnekar, Ramesh Harjani, Jiang Hu:
A Circuit Attention Network-Based Actor-Critic Learning Approach to Robust Analog Transistor Sizing. 1-6 - Erika S. Alcorta, Andreas Gerstlauer:
Learning-Based Workload Phase Classification and Prediction Using Performance Monitoring Counters. 1-6 - Mohamed Baker Alawieh, David Z. Pan:
ADAPT: An Adaptive Machine Learning Framework with Application to Lithography Hotspot Detection. 1-6 - Peng-Tai Huang, Xuan-Yi Lin, Yan-Jhih Wang, Tsung-Yi Ho:
Ensemble Learning Based Electric Components Footprint Analysis. 1-6 - Raviv Gal, Eldad Haber, Brian Irwin, Marwa Mouallem, Bilal Saleh, Avi Ziv:
Using Deep Neural Networks And Derivative Free Optimization To Accelerate Coverage Closure. 1-6 - Timothy Martin, Shawki Areibi, Gary Gréwal:
Effective Machine-Learning Models for Predicting Routability During FPGA Placement. 1-6 - Ahsan Saeed, Daniel Mueller-Gritschneder, Falk Rehm, Arne Hamann, Dirk Ziegenbein, Ulf Schlichtmann, Andreas Gerstlauer:
Learning based Memory Interference Prediction for Co-running Applications on Multi-Cores. 1-6 - Veera Venkata Ram Murali Krishna Rao Muvva, Martin Rapp, Jörg Henkel, Hussam Amrouch, Marilyn Wolf:
On the Effectiveness of Quantization and Pruning on the Performance of FPGAs-based NN Temperature Estimation. 1-7 - Jan Spieck, Stefan Wildermann, Jürgen Teich:
Domain-Adaptive Soft Real-Time Hybrid Application Mapping for MPSoCs. 1-6 - Zhengfeng Wu, Ioannis Savidis:
Variation-aware Analog Circuit Sizing with Classifier Chains. 1-6 - Kuan-Chun Chen, Chou-Chen Lee, Mark Po-Hung Lin, Yan-Jhih Wang, Yi-Ting Chen:
Massive Figure Extraction and Classification in Electronic Component Datasheets for Accelerating PCB Design Preparation. 1-6 - Hishan Parry, Lei Xun, Amin Sabet, Jia Bi, Jonathon S. Hare, Geoff V. Merrett:
Dynamic Transformer for Efficient Machine Translation on Embedded Devices. 1-6 - Madhvi Agarwal, Sneh Saurabh:
An Efficient Timing Model of Flip-Flops Based on Artificial Neural Network. 1-6 - Felix Last, Ulf Schlichtmann:
Feeding Hungry Models Less: Deep Transfer Learning for Embedded Memory PPA Models : Special Session. 1-6 - Mohamed Saleh Abouelyazid, Sherif Hammouda, Yehea Ismail:
Connectivity-Based Machine Learning Compact Models for Interconnect Parasitic Capacitances. 1-6 - Zixuan Jiang, Ebrahim M. Songhori, Shen Wang, Anna Goldie, Azalia Mirhoseini, Joe W. J. Jiang, Young-Joon Lee, David Z. Pan:
Delving into Macro Placement with Reinforcement Learning. 1-3 - Subed Lamichhane, Shaoyi Peng, Wentian Jin, Sheldon X.-D. Tan:
Fast Electrostatic Analysis For VLSI Aging based on Generative Learning. 1-6
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