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Spiking Neural Network Dataset
The dataset used in this paper is a spiking neural network (SNN) with 20 layers, where each layer has 2000 LIF neurons. The input spikes are Poisson trains at a target rate of... -
Towards stable and efficient training of verifiably robust neural networks
A method for learning models robust to adversarial examples. -
Deep learning for 3D building reconstruction: A review
Deep learning for 3D building reconstruction: A review -
Deep Learning Models
The dataset used in this paper is a set of 20 well-known deep-learning models, including AlexNet, ResNet, VGG, DenseNet, etc. -
DASA: Domain Adaptation in Stacked Autoencoders using Systematic Dropout
The paper proposes a technique for domain adaptation in stacked autoencoders using systematic dropout. -
Learning the number of neurons in deep networks
Learning the number of neurons in deep networks. -
Hardware-Aware Latency Pruning
The proposed hardware-aware latency pruning (HALP) paradigm. Considering both performance and latency contributions, HALP formulates global structural pruning as a global... -
PERMUTOHEDRAL LATTICE CONVOLUTION
The permutohedral lattice convolution is used to process sparse input features, allowing for efficient filtering of signals that do not lie on a dense grid. -
ResNet18 dataset
The dataset used in the paper is the ResNet18 dataset, which is a convolutional neural network dataset. -
Joint Visual Denoising and Classification Using Deep Learning
Visual restoration and recognition are traditionally addressed in pipeline fashion, i.e. denoising followed by classification. Instead, observing correlations between the two... -
Atari 2600 games
The dataset used in this paper is a collection of state-action pairs generated by a pre-trained RL agent, used to train a self-supervised interpretable network (SSINet) to... -
Progressive Feedforward Collapse of ResNet Training
The dataset used in the paper is a ResNet trained on various datasets, including MNIST, Fashion MNIST, CIFAR10, STL10, and CIFAR100. -
COVID-CT-Dataset: a CT scan dataset about COVID-19
A CT scan dataset about COVID-19 -
COVID-VIT: Classification of Covid-19 from CT chest images based on vision tr...
COVID-19 classification from CT chest images based on vision transformer models -
Towards Principled Causal Effect Estimation by Deep Identifiable Models
The dataset used in the paper for causal effect estimation using Intact-VAE. -
Automating sleep scoring in mice with deep learning
Reliable automation of the labor-intensive manual task of scoring animal sleep can facilitate the analysis of long-term sleep studies. -
ImageNet and Wiki103
The dataset used in the paper is ImageNet and Wiki103. -
ImageNet + ResNet101 and WT103 + TransformerXL models
The dataset used in the paper is ImageNet + ResNet101 and WT103 + TransformerXL models. -
Tied Block Convolution: Leaner and Better CNNs with Shared Thinner Filters
Convolution is the main building block of convolutional neural networks (CNN). We observe that an optimized CNN often has highly correlated filters as the number of channels...
