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CASCADE ADVERSARIAL MACHINE LEARNING REGULARIZED WITH A UNIFIED EMBEDDING
The dataset used in the paper is MNIST and CIFAR10. -
Discriminative Deep Forest (DisDF)
A Discriminative Deep Forest (DisDF) as a metric learning algorithm is proposed in the paper. -
Pong Variants
The dataset used in the paper is a set of Pong variants, including Noisy, Black, White, Zoom, and others. -
3D Maze Games
The dataset used in the paper is a set of 3D maze games, including Labyrinth and others. -
Learning Trajectories are Generalization Indicators
This paper explores the connection between learning trajectories of Deep Neural Networks (DNNs) and their generalization capabilities when optimized using stochastic gradient... -
Negative Correlation Ensemble for Adversarial Examples Defense
The FashionMNIST and CIFAR-10 datasets are used to evaluate the performance of the Negative Correlation Ensemble (NCEn) defense strategy. -
Physics-informed neural network solution of thermo-hydro-mechanical (THM) pro...
Physics-Informed Neural Networks (PINNs) have received increased interest for forward, inverse, and surrogate modeling of problems described by partial differential equations... -
Leapfrogging for parallelism in deep neural networks
The dataset used in the paper is a neural network with L layers numbered 1,..., L, in which each of the hidden layers has N neurons. -
Catalog of Visual-like Morphologies
A catalog of visual-like morphologies in the 5 Candels fields using deep-learning -
SDSS Galaxy Morphology Catalog
A catalog of broad morphology of SDSS galaxies -
Pan-STARRS morphology catalog
A catalog of broad morphology of Pan-STARRS galaxies based on deep learning -
NITI: INTEGER TRAINING
The dataset used in this paper is MNIST, CIFAR10, and ImageNet. -
Batch Inverse-Variance Weighting: Deep Heteroscedastic Regression
Heteroscedastic regression is the task of supervised learning where each label is subject to noise from a different distribution. This noise can be caused by the labelling... -
SolarNet: A Deep Learning Framework to Map Solar Power Plants in China from S...
A deep learning framework to map solar power plants from large-scale satellite imagery data -
Deep Meta Functionals for Shape Representation
A new method for 3D shape reconstruction from a single image, in which a deep neural network directly maps an image to a vector of network weights. -
Parking Analytics Framework using Deep Learning
A dataset for parking analytics using deep learning and image processing. -
Binary Bits Dataset
The dataset used in this paper is a collection of binary bits, turbo encoded and decoded using the proposed RNN architecture. -
Simulation Framework for Turbo Encoding and Decoding
The dataset used in this paper is a simulation framework for turbo encoding and decoding operations. It consists of four autoencoding problems: one for encoding and three for... -
Urban Street Tree Inventory with Deep Learning on Mobile Phone Imagery
A comprehensive dataset of 400 images of tree trunks, used for training and testing the proposed method for diameter at breast height (DBH) estimation. -
ILMPQ: An Intra-Layer Multi-Precision Deep Neural Network Quantization framew...
ILMPQ: An Intra-Layer Multi-Precision Deep Neural Network Quantization framework for FPGA
