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ORCIDAhmet Faruk Budak
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2020 – today
- 2024
[c7]Supriyo Maji
, Ahmet Faruk Budak, Souradip Poddar, David Z. Pan:
Toward End-to-End Analog Design Automation with ML and Data-Driven Approaches (Invited Paper). ASPDAC 2024: 657-664- [c6]Souradip Poddar, Ahmet Faruk Budak, Linran Zhao, Chen-Hao Hsu, Supriyo Maji, Keren Zhu, Yaoyao Jia, David Z. Pan:
A Data-Driven Analog Circuit Synthesizer with Automatic Topology Selection and Sizing. DATE 2024: 1-6 - 2023
- [c5]Ahmet Faruk Budak, David Smart, Brian Swahn, David Z. Pan:
APOSTLE: Asynchronously Parallel Optimization for Sizing Analog Transistors Using DNN Learning. ASP-DAC 2023: 70-75 - [c4]Ahmet Faruk Budak, Keren Zhu, David Z. Pan:
Practical Layout-Aware Analog/Mixed-Signal Design Automation with Bayesian Neural Networks. ICCAD 2023: 1-8 - [c3]Ahmet Faruk Budak, Keren Zhu, Hao Chen, Souradip Poddar, Linran Zhao, Yaoyao Jia, David Z. Pan:
Joint Optimization of Sizing and Layout for AMS Designs: Challenges and Opportunities. ISPD 2023: 84-92 - [i2]Ahmet Faruk Budak, Keren Zhu, David Z. Pan:
Practical Layout-Aware Analog/Mixed-Signal Design Automation with Bayesian Neural Networks. CoRR abs/2311.17073 (2023) - 2022
- [j1]Ahmet Faruk Budak, Miguel Gandara, Wei Shi, David Z. Pan, Nan Sun, Bo Liu:
An Efficient Analog Circuit Sizing Method Based on Machine Learning Assisted Global Optimization. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(5): 1209-1221 (2022) - [c2]Ahmet Faruk Budak, Zixuan Jiang, Keren Zhu, Azalia Mirhoseini, Anna Goldie, David Z. Pan:
Reinforcement Learning for Electronic Design Automation: Case Studies and Perspectives: (Invited Paper). ASP-DAC 2022: 500-505 - 2021
- [c1]Ahmet Faruk Budak, Prateek Bhansali, Bo Liu, Nan Sun, David Z. Pan, Chandramouli V. Kashyap:
DNN-Opt: An RL Inspired Optimization for Analog Circuit Sizing using Deep Neural Networks. DAC 2021: 1219-1224 - [i1]Ahmet Faruk Budak, Prateek Bhansali, Bo Liu, Nan Sun, David Z. Pan, Chandramouli V. Kashyap:
DNN-Opt: An RL Inspired Optimization for Analog Circuit Sizing using Deep Neural Networks. CoRR abs/2110.00211 (2021)
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