The following pages link to ImageNet (Q32917):
Displaying 50 items.
- Data-driven fault monitoring for spacecraft control moment gyro with slice residual attention network (Q2095015) (← links)
- Stochastic modeling of inhomogeneities in the aortic wall and uncertainty quantification using a Bayesian encoder-decoder surrogate (Q2096832) (← links)
- An outer-approximation guided optimization approach for constrained neural network inverse problems (Q2097633) (← links)
- Numerical modelling of reservoir at pore scale: a comprehensive review (Q2099732) (← links)
- A capsule-unified framework of deep neural networks for graphical programming (Q2099868) (← links)
- Ear-based authentication using information sets and information modelling (Q2100273) (← links)
- Task-specific loss: a teacher-centered approach to transfer learning between distinctly structured robotic agents (Q2101736) (← links)
- Model free error compensation for cable-driven robot based on deep learning with sim2real transfer learning (Q2101780) (← links)
- Semi-supervised semantic segmentation in Earth observation: the MiniFrance suite, dataset analysis and multi-task network study (Q2102368) (← links)
- Pruning convolutional neural networks via filter similarity analysis (Q2102371) (← links)
- Towards harnessing feature embedding for robust learning with noisy labels (Q2102373) (← links)
- Stateless neural meta-learning using second-order gradients (Q2102379) (← links)
- An adaptive Polyak heavy-ball method (Q2102380) (← links)
- Tackling algorithmic bias in neural-network classifiers using Wasserstein-2 regularization (Q2103876) (← links)
- Recurrence of optimum for training weight and activation quantized networks (Q2105102) (← links)
- Stable recovery of entangled weights: towards robust identification of deep neural networks from minimal samples (Q2105108) (← links)
- Parameter synthesis of polynomial dynamical systems (Q2105425) (← links)
- A measure theoretical approach to the mean-field maximum principle for training NeurODEs (Q2105521) (← links)
- Multi-granularity sequential three-way recommendation based on collaborative deep learning (Q2105630) (← links)
- Optimal control of PDEs using physics-informed neural networks (Q2106939) (← links)
- Median arc center corrected binary pattern (MACCBP) for noise robust feature extraction (Q2108466) (← links)
- Approximation of functions from korobov spaces by deep convolutional neural networks (Q2108977) (← links)
- Binary quantized network training with sharpness-aware minimization (Q2111176) (← links)
- On neural network equivalence checking using SMT solvers (Q2112128) (← links)
- Analysis of convolutional neural network image classifiers in a hierarchical max-pooling model with additional local pooling (Q2112261) (← links)
- Multiresolution convolutional autoencoders (Q2112504) (← links)
- Prediction of optical solitons using an improved physics-informed neural network method with the conservation law constraint (Q2113135) (← links)
- The nonlinear wave solutions and parameters discovery of the Lakshmanan-Porsezian-Daniel based on deep learning (Q2113140) (← links)
- A weighted wrapper approach to feature selection (Q2115924) (← links)
- Bridging the gap: machine learning to resolve improperly modeled dynamics (Q2116291) (← links)
- CECMLP: new cipher-based evaluating collaborative multi-layer perceptron scheme in federated learning (Q2117030) (← links)
- Nonlinear approximation and (deep) ReLU networks (Q2117331) (← links)
- Neural network identifiability for a family of sigmoidal nonlinearities (Q2117333) (← links)
- Approximation spaces of deep neural networks (Q2117336) (← links)
- Robust and resource-efficient identification of two hidden layer neural networks (Q2117339) (← links)
- Best \(k\)-layer neural network approximations (Q2117342) (← links)
- On the thermodynamic interpretation of deep learning systems (Q2117965) (← links)
- Wide-angle image rectification: a survey (Q2118430) (← links)
- Solving inverse problems using conditional invertible neural networks (Q2120777) (← links)
- On the antiderivatives of \(x^p/(1 - x)\) with an application to optimize loss functions for classification with neural networks (Q2122774) (← links)
- Meta-learning pseudo-differential operators with deep neural networks (Q2123371) (← links)
- Black-box adversarial attacks by manipulating image attributes (Q2123528) (← links)
- Neural software vulnerability analysis using rich intermediate graph representations of programs (Q2123552) (← links)
- A neural network based shock detection and localization approach for discontinuous Galerkin methods (Q2123860) (← links)
- A probabilistic generative model for semi-supervised training of coarse-grained surrogates and enforcing physical constraints through virtual observables (Q2124009) (← links)
- The data-driven localized wave solutions of the derivative nonlinear Schrödinger equation by using improved PINN approach (Q2124077) (← links)
- Cross-class generative network for zero-shot learning (Q2124180) (← links)
- Multi-view graph convolutional networks with attention mechanism (Q2124471) (← links)
- Pruning deep convolutional neural networks architectures with evolution strategy (Q2126266) (← links)
- Structure-preserving neural networks (Q2127014) (← links)
