Pages that link to "Item:Q2146912"
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The following pages link to Learning generative neural networks with physics knowledge (Q2146912):
Displaying 11 items.
- GANs for generating EFT models (Q823097) (← links)
- Learning functional priors and posteriors from data and physics (Q2135824) (← links)
- Adversarial uncertainty quantification in physics-informed neural networks (Q2222278) (← links)
- Coercing machine learning to output physically accurate results (Q2223280) (← links)
- Prediction and identification of physical systems by means of physically-guided neural networks with meaningful internal layers (Q2236964) (← links)
- Conditional physics informed neural networks (Q2247060) (← links)
- Enforcing Imprecise Constraints on Generative Adversarial Networks for Emulating Physical Systems (Q5163887) (← links)
- Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations (Q5214836) (← links)
- Observing how deep neural networks understand physics through the energy spectrum of 1D quantum mechanics (Q5878030) (← links)
- Probabilistic partition of unity networks for high‐dimensional regression problems (Q6062830) (← links)
- SDYN-GANs: adversarial learning methods for multistep generative models for general order stochastic dynamics (Q6639347) (← links)
