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Found 7 papers, 2 papers with code
Dimension Mixer: A Generalized Method for Structured Sparsity in Deep Neural Networks
The recent success of multiple neural architectures like CNNs, Transformers, and MLP-Mixers motivated us to look for similarities and differences between them.
Importance Estimation with Random Gradient for Neural Network Pruning
Global Neuron Importance Estimation is used to prune neural networks for efficiency reasons.
Neural Network Pruning for Real-time Polyp Segmentation
In this study, we show an application of neural network pruning in polyp segmentation.
Noisy Heuristics NAS: A Network Morphism based Neural Architecture Search using Heuristics
Network Morphism based Neural Architecture Search (NAS) is one of the most efficient methods, however, knowing where and when to add new neurons or remove dis-functional ones is generally left to black-box Reinforcement Learning models.
Brand Label Albedo Extraction of eCommerce Products using Generative Adversarial Network
In this paper we present our solution to extract albedo of branded labels for e-commerce products.
Input Invex Neural Network
In the experiments section, we use our methods for classification tasks using an ensemble of 1-vs-all models as well as using a single multiclass model on larger-scale datasets.
Label Geometry Aware Discriminator for Conditional Generative Networks
Multi-domain image-to-image translation with conditional Generative Adversarial Networks (GANs) can generate highly photo realistic images with desired target classes, yet these synthetic images have not always been helpful to improve downstream supervised tasks such as image classification.
