Pages that link to "Item:Q2205158"
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The following pages link to Topology optimization based on deep representation learning (DRL) for compliance and stress-constrained design (Q2205158):
Displaying 25 items.
- Reverse shape compensation via a gradient-based moving particle optimization method (Q2021930) (← links)
- Universal machine learning for topology optimization (Q2022034) (← links)
- De-homogenization using convolutional neural networks (Q2060089) (← links)
- Data-driven multifidelity topology design using a deep generative model: application to forced convection heat transfer problems (Q2060177) (← links)
- IGA-reuse-NET: a deep-learning-based isogeometric analysis-reuse approach with topology-consistent parameterization (Q2139715) (← links)
- Deep reliability learning with latent adaptation for design optimization under uncertainty (Q2145132) (← links)
- IH-GAN: a conditional generative model for implicit surface-based inverse design of cellular structures (Q2156772) (← links)
- Machine learning for topology optimization: physics-based learning through an independent training strategy (Q2160385) (← links)
- An efficient 146-line 3D sensitivity analysis code of stress-based topology optimization written in Matlab (Q2168645) (← links)
- TONR: an exploration for a novel way combining neural network with topology optimization (Q2246269) (← links)
- Accurate and real-time structural topology prediction driven by deep learning under moving morphable component-based framework (Q2247294) (← links)
- Artificial neural network based hole image interpretation techniques for integrated topology and shape optimization (Q2493814) (← links)
- Robust topology optimization with low rank approximation using artificial neural networks (Q2667321) (← links)
- Isogeometric topology optimization based on deep learning (Q2674045) (← links)
- Optimum design of nonlinear structures via deep neural network-based parameterization framework (Q2691035) (← links)
- Deep energy method in topology optimization applications (Q2694685) (← links)
- Structural Topology Optimization by Combining BESO with Reinforcement Learning (Q3381142) (← links)
- Cross-resolution acceleration design for structural topology optimization based on deep learning (Q3385176) (← links)
- Deep learning driven real time topology optimization based on improved convolutional block attention (Cba-U-Net) model (Q6042422) (← links)
- A deep convolutional neural network for topology optimization with perceptible generalization ability (Q6048164) (← links)
- Topology optimization via implicit neural representations (Q6097597) (← links)
- Material Design with Topology Optimization Based on the Neural Network (Q6173001) (← links)
- TO-NODE: topology optimization with neural ordinary differential equation (Q6499906) (← links)
- A density-based boundary evolving method for buckling-induced design under large deformation (Q6553324) (← links)
- Deep learning in computational mechanics: a review (Q6604128) (← links)
