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Framework for In-memory Computing based on Memristor and Memcapacitor for On-...
A comprehensive Python framework for evaluating large-scale deep neural networks (DNN) on memristive and memcapacitive crossbar systems, addressing various non-idealities. -
Depth Separation with Intra-layer Links
The dataset used in the paper is a collection of functions that can be represented by a deep network, but cannot be represented by a shallow network. -
DeepLIFT: Learning Important Features Through Propagating Activation Differences
DeepLIFT is a method for assigning feature importance that compares a neuron's activation to its'reference', where the reference is the activation that the neuron has when the... -
Spatio-Temporal Graph Transformer Networks for Pedestrian Trajectory Prediction
This paper introduces STAR, a framework for spatio-temporal crowd trajectory prediction with only attention mechanisms. -
Hamiltonian Neural Networks
The dataset is used for learning Hamiltonian neural networks. -
PANGAEA search space
A dataset of 425,896 unique activation functions, created using the PANGAEA search space. -
Act-Bench-CNN, Act-Bench-ResNet, and Act-Bench-ViT
Three benchmark datasets: Act-Bench-CNN, Act-Bench-ResNet, and Act-Bench-ViT, created by training convolutional, residual, and vision transformer architectures from scratch with... -
MnasNet: In platform-aware neural architecture search for mobile
MnasNet: In platform-aware neural architecture search for mobile -
UNAS: Differentiable Architecture Search Meets Reinforcement Learning
UNAS: Differentiable Architecture Search Meets Reinforcement Learning -
Learning the number of neurons in deep networks
Learning the number of neurons in deep networks. -
Heat Equation, Burgers Equation, and Kuramoto-Sivashinsky Equation Datasets
The dataset used for training and testing the neural network for linearizing the heat equation, Burgers equation, and Kuramoto-Sivashinsky equation. -
Answer Sequence Learning with Neural Networks for Answer Selection in Communi...
Answer selection in community question answering (CQA) is regarded as an answer sequence label-ling task, and a novel approach is proposed based on the recurrent architecture... -
Neural Joint Source-Channel Coding
The dataset used in the paper for neural joint source-channel coding. -
Interpretable Neural Network Decoupling
The proposed neural network decoupling approach enables a network to adaptively select a suitable subset of filters to form a calculation path for each input. -
Brain-Score
A large-scale benchmark for evaluating the brain-likeness of neural networks. -
BrainScaleS-2
The BrainScaleS-2 system is used for analog inference acceleration. -
VGG16-D dataset
The VGG16-D dataset is a large dataset of images, used for training and testing neural networks. -
Indoor Environment Data Time-Series Reconstruction Using Autoencoder
The dataset used in this paper is a collection of indoor environment data time-series, including temperature, relative humidity, and CO2 concentration. -
Neural 3D Video Synthesis
Neural 3D Video Synthesis dataset contains 3D videos synthesized using neural networks.
