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Discontinuous Neural Network for Non-Negative Sparse Approximation
The dataset is used to model the mammalian olfactory system and solve non-negative sparse approximation problems. -
Show-and-Tell
Visual language grounding is widely studied in modern neural networks, which typically adopts an encoder-decoder framework consisting of a convolutional neural network (CNN) for... -
Coexistence of fast and slow gamma oscillations
The dataset describes the coexistence of fast and slow gamma oscillations in a single inhibitory population of neurons. -
Neural Lattice Reduction
The dataset used in the paper is a randomly-generated dataset of lattices, where each lattice is represented by a basis of n vectors in R^n. -
Discovery of Dynamics via Deep Learning
The dataset used in the paper is a collection of time series data from a dynamical system, which is used to test the performance of the network-based LMMs for discovering... -
Synthesis of Neural Barrier Certificates
The dataset used in the paper is a set of polynomial and non-polynomial dynamical models, including the Darboux model, the exponential model, the obstacle avoidance problem, the... -
Neural Identification for Control
The proposed method for learning control for an unknown nonlinear dynamical system by formulating a system identification task. -
Elliptic Optimal Control Problems
The dataset used in this paper is a collection of examples for testing the proposed neural solver for distributed elliptic optimal control problems. -
Neural network-based acoustic vehicle counting
Acoustic vehicle counting using one-channel audio. We predict the pass-by instants of vehicles from local minima of clipped vehicle-to-microphone distance. -
ExNN Dataset
ExNN dataset used for credit default prediction -
Stability Verification in Stochastic Control Systems via Neural Network
The dataset used in the paper is a discrete-time stochastic dynamical system with two novel aspects: (a) using ranking supermartingales (RSMs) to certify almost-sure asymptotic... -
Efficient and Robust Classification for Sparse Attacks
The MNIST and CIFAR datasets are used to test the robustness of neural networks against sparse attacks. -
Character-Aware Neural Networks for Word-Level Prediction: Do They Discover L...
Character-level features are currently used in different neural network-based natural language processing algorithms. However, little is known about the character-level patterns... -
pulse2percept dataset
The dataset used in this paper is a simulation dataset for retinal prosthetic stimulation optimization. It contains 10,000,000 random stimulus-percept pairs and is used to... -
CuratorNet: Visually-aware Recommendation of Art Images
A neural network architecture for visually-aware recommendation of art images. -
Simulated neural networks and larval zebrafish imaging
Simulated neural networks and larval zebrafish imaging data -
Binary Neural Network Dataset
The dataset used in this paper is a binary neural network model. -
Tangent Bundle Neural Networks
The dataset is used to test the performance of Tangent Bundle Neural Networks on three tasks: denoising of a tangent vector field on the torus, reconstruction from partial... -
DIV2K, Flickr2K, and CLIC datasets
The dataset used in the paper for neural image compression.