Pages that link to "Item:Q689479"
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The following pages link to Backpropagation and stochastic gradient descent method (Q689479):
Displaying 18 items.
- Deep learning nonlinear multiscale dynamic problems using Koopman operator (Q2133546) (← links)
- (Q5013261) (← links)
- Identification and prediction of time-varying parameters of COVID-19 model: a data-driven deep learning approach (Q5031306) (← links)
- Advanced Lectures on Machine Learning (Q5424899) (← links)
- Inverse design of phononic crystals for anticipated wave propagation by integrating deep learning and semi-analytical approach (Q6074788) (← links)
- Continuous interval type‐2 fuzzy Q‐learning algorithm for trajectory tracking tasks for vehicles (Q6085460) (← links)
- Machine learning-based conditional mean filter: a generalization of the ensemble Kalman filter for nonlinear data assimilation (Q6154247) (← links)
- Optimal parameters selection of back propagation algorithm in the feedforward neural network (Q6158709) (← links)
- A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning (Q6195318) (← links)
- Gradient preserving operator inference: data-driven reduced-order models for equations with gradient structure (Q6557793) (← links)
- Compressive strength prediction of high-performance hydraulic concrete using a novel neural network based on the memristor (Q6578105) (← links)
- An immersed boundary fast meshfree integration methodology with consistent weight learning (Q6588273) (← links)
- Multiscale graph neural networks with adaptive mesh refinement for accelerating mesh-based simulations (Q6588310) (← links)
- Class incremental learning with KL constraint and multi-strategy exemplar selection for classification based on MMFA model (Q6588432) (← links)
- A meshless solver for blood flow simulations in elastic vessels using a physics-informed neural network (Q6590130) (← links)
- Reds: random ensemble deep spatial prediction (Q6626548) (← links)
- Fredholm integral equations for function approximation and the training of neural networks (Q6655076) (← links)
- Full 3D blood flow simulation in curved deformable vessels using physics-informed neural networks (Q6667283) (← links)
