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20212026
most citedPcDGAN: A Continuous Conditional Diverse Generative Adversarial Network For Inverse Design

15 citations · 17 across the 5 of their papers we have counts for

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cs.LG2026

GIFT: Bootstrapping Image-to-CAD Program Synthesis via Geometric Feedback

Giorgio Giannone, Anna Clare Doris, Amin Heyrani Nobari +3

Generating executable CAD programs from images requires alignment between visual geometry and symbolic program representations, a capability that current methods fail to learn reli…

cs.LG2025

Optimize Any Topology: A Foundation Model for Shape- and Resolution-Free Structural Topology Optimization

Amin Heyrani Nobari, Lyle Regenwetter, Cyril Picard +2

Structural topology optimization (TO) is central to engineering design but remains computationally intensive due to complex physics and hard constraints. Existing deep-learning met…

cs.LG2024

LInK: Learning Joint Representations of Design and Performance Spaces through Contrastive Learning for Mechanism Synthesis

Amin Heyrani Nobari, Akash Srivastava, Dan Gutfreund +2

In this paper, we introduce LInK, a novel framework that integrates contrastive learning of performance and design space with optimization techniques for solving complex inverse pr…

cs.LG20241 cited

NITO: Neural Implicit Fields for Resolution-free Topology Optimization

Amin Heyrani Nobari, Giorgio Giannone, Lyle Regenwetter +1

Topology optimization is a critical task in engineering design, where the goal is to optimally distribute material in a given space for maximum performance. We introduce Neural Imp…

cs.LG202115 cited

PcDGAN: A Continuous Conditional Diverse Generative Adversarial Network For Inverse Design

Amin Heyrani Nobari, Wei Chen, Faez Ahmed

Engineering design tasks often require synthesizing new designs that meet desired performance requirements. The conventional design process, which requires iterative optimization a…

cs.LG20211 cited

CreativeGAN: Editing Generative Adversarial Networks for Creative Design Synthesis

Amin Heyrani Nobari, Muhammad Fathy Rashad, Faez Ahmed

Modern machine learning techniques, such as deep neural networks, are transforming many disciplines ranging from image recognition to language understanding, by uncovering patterns…