Analog IC Placement Generation via Neural Networks from Unlabeled Data - António Gusmão 001; Nuno Horta; Nuno Lourenço 003; Ricardo Martins 003 (Springer, 2020)

Semi-Supervised Artificial Neural Networks towards Analog IC Placement Recommender. - António Gusmão 001; Fábio Passos; Ricardo Póvoa; Nuno Horta; Nuno Lourenço 003; Ricardo Martins 003 (ISCAS, 2020)

Late Breaking Results: Attention in Graph2Seq Neural Networks towards Push-Button Analog IC Placement. - António Gusmão 001; Nuno Horta; Nuno Lourenço 003; Ricardo Martins 003 (DAC, 2021)

Speeding-Up Complex RF IC Sizing Optimizations with a Process, Voltage and Temperature Corner Performance Estimator based on ANNs. - Pedro Vaz; António Gusmão 001; Nuno Horta; Nuno Lourenço 003; Ricardo Martins 003 (ISCAS, 2022)

ANN-based Analog IC Floorplan Recommender with a Broader Topological Constraints Coverage. - Pedro Alves; António Gusmão 001; Nuno Horta; Nuno Lourenço 003; Ricardo Martins 003 (SMACD, 2022)

Accelerating Voltage-Controlled Oscillator Sizing Optimizations with ANN-based Convergence Classifiers and Frequency Guess Predictors. - João Domingues; António Gusmão 001; Nuno Horta; Nuno Lourenço 003; Ricardo Martins 003 (SMACD, 2022)

DeepPlacer: A custom integrated OpAmp placement tool using deep models. - António Gusmão 001; Ricardo Póvoa; Nuno Horta; Nuno Lourenço 003; Ricardo Martins 003 (Appl. Soft Comput., 2022)

Scalable and order invariant analog integrated circuit placement with Attention-based Graph-to-Sequence deep models. - António Paiva Lapas de Gusmão; Nuno Cavaco Gomes Horta; Nuno Calado Correia Lourenço; Ricardo Miguel Ferreira Martins (Expert Syst. Appl., 2022)

An ANN-Based Approach to the Modelling and Simulation of Analogue Circuits. - André Amaral; António Gusmão 001; Rafael Vieira; Ricardo Martins 003; Nuno Horta; Nuno Lourenço 003 (SMACD, 2023)

Ponderous: A Performance-driven Analog IC Placement Optimizer Leveraged by a ML Pipeline. - Ricardo Martins 003; António Gusmão 001; Rafael Vieira; Fábio Passos; Nuno Lourenço 003; Nuno Horta (SMACD, 2024)