The following pages link to ImageNet (Q32917):
Displaying 50 items.
- Three-way decisions based blocking reduction models in hierarchical classification (Q2663533) (← links)
- An information-theoretic instance-based classifier (Q2666796) (← links)
- Drop-activation: implicit parameter reduction and harmonious regularization (Q2667354) (← links)
- Learning the mapping \(\mathbf{x}\mapsto \sum\limits_{i=1}^d x_i^2\): the cost of finding the needle in a haystack (Q2667355) (← links)
- Logic tensor networks (Q2667828) (← links)
- Comprehensive analysis of embeddings and pre-training in NLP (Q2668408) (← links)
- High Reynolds number airfoil turbulence modeling method based on machine learning technique (Q2670056) (← links)
- A deep learning approach for the transonic flow field predictions around airfoils (Q2670066) (← links)
- Wasserstein generative adversarial uncertainty quantification in physics-informed neural networks (Q2671386) (← links)
- A hybrid inference system for improved curvature estimation in the level-set method using machine learning (Q2671404) (← links)
- Physics and equality constrained artificial neural networks: application to forward and inverse problems with multi-fidelity data fusion (Q2671417) (← links)
- A machine learning framework for LES closure terms (Q2672196) (← links)
- Decomposition and composition of deep convolutional neural networks and training acceleration via sub-network transfer learning (Q2672198) (← links)
- A hybrid objective function for robustness of artificial neural networks -- estimation of parameters in a mechanical system (Q2672200) (← links)
- ModalPINN: an extension of physics-informed neural networks with enforced truncated Fourier decomposition for periodic flow reconstruction using a limited number of imperfect sensors (Q2672754) (← links)
- Complexity of training ReLU neural network (Q2673242) (← links)
- CMD: controllable matrix decomposition with global optimization for deep neural network compression (Q2673311) (← links)
- Exploring the common principal subspace of deep features in neural networks (Q2673330) (← links)
- Towards interpreting deep neural networks via layer behavior understanding (Q2673336) (← links)
- Isogeometric topology optimization based on deep learning (Q2674045) (← links)
- Scalable uncertainty quantification for deep operator networks using randomized priors (Q2674111) (← links)
- Variational convolutional neural networks classifiers (Q2675928) (← links)
- Estimation of a regression function on a manifold by fully connected deep neural networks (Q2676904) (← links)
- Deep limits of residual neural networks (Q2679108) (← links)
- Deep CNNs as universal predictors of elasticity tensors in homogenization (Q2679501) (← links)
- Accelerating algebraic multigrid methods via artificial neural networks (Q2679755) (← links)
- Data-driven soliton mappings for integrable fractional nonlinear wave equations via deep learning with Fourier neural operator (Q2679950) (← links)
- \( \mathcal{G} \)-LIME: statistical learning for local interpretations of deep neural networks using global priors (Q2680795) (← links)
- Rationalizing predictions by adversarial information calibration (Q2680803) (← links)
- Manifold learning for coherent design interpolation based on geometrical and topological descriptors (Q2683444) (← links)
- Prediction of permeability of porous media using optimized convolutional neural networks (Q2683510) (← links)
- Optimization of artificial neural networks models applied to the identification of images of asteroids' resonant arguments (Q2685201) (← links)
- DeepCyto: a hybrid framework for cervical cancer classification by using deep feature fusion of cytology images (Q2686787) (← links)
- An improved self-supervised learning for EEG classification (Q2686826) (← links)
- On the influence of over-parameterization in manifold based surrogates and deep neural operators (Q2687573) (← links)
- Data-driven forward and inverse problems for chaotic and hyperchaotic dynamic systems based on two machine learning architectures (Q2688074) (← links)
- A hybrid control strategy for a dynamic scheduling problem in transit networks (Q2689048) (← links)
- The universal approximation theorem for complex-valued neural networks (Q2689134) (← links)
- Convex and concave envelopes of artificial neural network activation functions for deterministic global optimization (Q2689856) (← links)
- Maliciously secure matrix multiplication with applications to private deep learning (Q2691579) (← links)
- An unsupervised latent/output physics-informed convolutional-LSTM network for solving partial differential equations using peridynamic differential operator (Q2693426) (← links)
- Frame regularization of a convolutional neural network in image-classification problems (Q2695092) (← links)
- Reachability is NP-complete even for the simplest neural networks (Q2695495) (← links)
- Automated feature selection procedure for particle jet classification (Q2698965) (← links)
- Solving traveltime tomography with deep learning (Q2699488) (← links)
- BI-GreenNet: learning Green's functions by boundary integral network (Q2699491) (← links)
- Study of phase transition of Potts model with domain adversarial neural network (Q2700729) (← links)
- An embedding of ReLU networks and an analysis of their identifiability (Q2700885) (← links)
- Estimation from pairwise comparisons: sharp minimax bounds with topology dependence (Q2810857) (← links)
- (Q2934045) (← links)
