Key papers

• Inverse design for robust inference in integrated computational spectrometry (2025)
  Wenchao Ma et al.
  4.47
• Double anticrossings induced by nonlinear magnon interactions (2026)
  Geil Emdi et al.
  4.39
• Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations (2026)
  Arthur Fyon et al.
  1.89
• Harnessing Photonics for Machine Intelligence (2026)
  Hanqing Zhu et al.
  1.83
• Generative Design for Direct-to-Chip Liquid Cooling for Data Centers (2026)
  Zheng Liu
  1.83
• Towards Efficient and Stable Ocean State Forecasting: A Continuous-Time Koopman Approach (2026)
  Rares Grozavescu et al.
  1.78
• Physics-Informed Framework for Impact Identification in Aerospace Composites (2026)
  Nat\'alia Ribeiro Marinho et al.
  1.78
• Democratizing Electronic-Photonic AI Systems: An Open-Source AI-Infused Cross-Layer Co-Design and Design Automation Toolflow (2026)
  Hongjian Zhou et al.
  1.67
• OSIRIS: Bridging Analog Circuit Design and Machine Learning with Scalable Dataset Generation (2026)
  Giuseppe Chiari et al.
  1.67
• Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade (2025)
  Letian Yi et al.
  1.61
• MaskOpt: A Large-Scale Mask Optimization Dataset to Advance AI in Integrated Circuit Manufacturing (2025)
  Yuting Hu et al.
  1.61
• DeepRWCap: Neural-Guided Random-Walk Capacitance Solver for IC Design (2025)
  Hector R. Rodriguez et al.
  1.56
• ZeroSim: Zero-Shot Analog Circuit Evaluation with Unified Transformer Embeddings (2025)
  Xiaomeng Yang et al.
  1.56
• MOTIF-RF: Multi-template On-chip Transformer Synthesis Incorporating Frequency-domain Self-transfer Learning for RFIC Design Automation (2025)
  Houbo He et al.
  1.56
• Hybrid unary-binary design for multiplier-less printed Machine Learning classifiers (2025)
  Giorgos Armeniakos et al.
  1.44
• RF-Informed Graph Neural Networks for Accurate and Data-Efficient Circuit Performance Prediction (2025)
  Anahita Asadi et al.
  1.39
• Photonic restricted Boltzmann machine for content generation tasks (2025)
  Li Luo et al.
  1.39
• DALI-PD: Diffusion-based Synthetic Layout Heatmap Generation for ML in Physical Design (2025)
  Bing-Yue Wu and Vidya A. Chhabria
  1.33
• Accelerating RF Power Amplifier Design via Intelligent Sampling and ML-Based Parameter Tuning (2025)
  Abhishek Sriram et al.
  1.33
• Emerging ML-AI Techniques for Analog and RF EDA (2025)
  Zhengfeng Wu et al.
  1.28
• FALCON: An ML Framework for Fully Automated Layout-Constrained Analog Circuit Design (2025)
  Asal Mehradfar et al.
  1.22
• Data-Driven Antenna Miniaturization: A Knowledge-Based System Integrating Quantum PSO and Predictive Machine Learning Models (2025)
  Khan Masood Parvez et al.
  1.22
• Estimating Voltage Drop: Models, Features and Data Representation Towards a Neural Surrogate (2025)
  Yifei Jin et al.
  1.06
• PICTS: A Novel Deep Reinforcement Learning Approach for Dynamic P-I Control in Scanning Probe Microscopy (2025)
  Ziwei Wei et al.
  1.06
• Supervised Learning for Analog and RF Circuit Design: Benchmarks and Comparative Insights (2025)
  Asal Mehradfar et al.
  1.00
• CktGen: Automated Analog Circuit Design with Generative Artificial Intelligence (2024)
  Yuxuan Hou et al.
  0.89
• Machine learning thermal circuit network model for thermal design optimization of electronic circuit board layout with transient heating chips (2020)
  Daiki Otaki (1) et al.
  —
• Analog/Mixed-Signal Circuit Synthesis Enabled by the Advancements of Circuit Architectures and Machine Learning Algorithms (2021)
  Shiyu Su et al.
  —
• Cross-Layer Approximation For Printed Machine Learning Circuits (2022)
  Giorgos Armeniakos et al.
  —
• Automated Circuit Sizing with Multi-objective Optimization based on Differential Evolution and Bayesian Inference (2022)
  Catalin Visan et al.
  —
• Intelligent Circuit Design and Implementation with Machine Learning (2022)
  Zhiyao Xie
  —
• Machine learning based surrogate models for microchannel heat sink optimization (2022)
  Ante Sikirica et al.
  —
• A Thermal Machine Learning Solver For Chip Simulation (2022)
  Rishikesh Ranade et al.
  —
• An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design (2022)
  Mingjie Liu et al.
  —
• Deep learning for size-agnostic inverse design of random-network 3D printed mechanical metamaterials (2022)
  Helda Pahlavani et al.
  —
• CMOS + stochastic nanomagnets: heterogeneous computers for probabilistic inference and learning (2023)
  Nihal Sanjay Singh et al.
  —
• Machine Learning and Kalman Filtering for Nanomechanical Mass Spectrometry (2023)
  Mete Erdogan et al.
  —
• Machine Learning-powered Compact Modeling of Stochastic Electronic Devices using Mixture Density Networks (2023)
  Jack Hutchins et al.
  —
• Deep learning for the design of non-Hermitian topolectrical circuits (2024)
  Xi Chen et al.
  —
• Meent: Differentiable Electromagnetic Simulator for Machine Learning (2024)
  Yongha Kim et al.
  —
• Machine Learning Assisted Design of mmWave Wireless Transceiver Circuits (2024)
  Xuzhe Zhao
  —
• A Roadmap to Holographic Focused Ultrasound Approaches to Generate Thermal Patterns (2024)
  Ceren Cengiz et al.
  —
• SimPhony: A Device-Circuit-Architecture Cross-Layer Modeling and Simulation Framework for Heterogeneous Electronic-Photonic AI System (2024)
  Ziang Yin et al.
  —
• Schemato -- An LLM for Netlist-to-Schematic Conversion (2024)
  Ryoga Matsuo et al.
  —
• Evolutionary Optimization for Designing Variational Quantum Circuits with High Model Capacity (2024)
  Samuel Yen-Chi Chen
  —