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H-Fac: Memory-Efficient Optimization with Factorized Hamiltonian Descent
The dataset used in this study is a benchmark for evaluating the performance of memory-efficient optimizers. -
End-to-end learning potentials for structured attribute prediction
Structured inference approach for multiple attribute prediction -
GLOBUS: GLObal Building heights for Urban Studies
A novel Level of Detail-1 (LoD-1) building dataset derived from a Deep Neural Network (DNN) called GLOBUS. -
Dense Depth Posterior (DDP) from Single Image and Sparse Range
A deep learning system to infer the posterior distribution of a dense depth map associated with an image, by exploiting sparse range measurements. -
GEEN Dataset
The dataset used in this paper is a sample of (X 1, X 2,..., X k, X ∗) where X ∗ is a latent variable. -
Clustered Data Distribution
The dataset consists of clusters with means µ(1),..., µ(k) and the examples in the j-th cluster are labeled by y(j). The clusters are generated as follows: we draw j ∼ U[0, 1]... -
Angiodysplasia Detection and Localization
A dataset for angiodysplasia detection and localization using deep convolutional neural networks. -
N-MNIST and SHD datasets
The dataset used for training and testing the accelerated ALIF SNN model. -
Frequency-driven Imperceptible Adversarial Attack on Semantic Similarity
The proposed framework, SSAH, for adversarial attack. It aims to perturb images by attacking their semantic similarity in representation space. -
SEVEN: Deep Semi-supervised Verification Networks
Verification determines whether two samples belong to the same class or not, and has important applications such as face and fingerprint verifica- tion, where thousands or millions... -
Airbnb Search Ranking
Airbnb search ranking dataset -
Deep learning optoacoustic tomography with sparse data
Deep learning optoacoustic tomography with sparse data -
Gait Data for Parkinson Disease Detection and Severity Prediction
The dataset used in this paper for Parkinson disease detection and severity prediction from gait data. -
Karyotype AI for Precision Oncology
A large-scale dataset of karyograms for hematological malignancies, used to train and evaluate a deep learning model for chromosome aberration detection. -
NuCLR: Nuclear Co-Learned Representations
NuCLR: Nuclear Co-Learned Representations, a deep learning model that predicts various nuclear observables, including binding and decay energies, and nuclear charge radii. -
Real Head Phantom Dataset
The dataset used for testing the proposed neural network for conebeam artifact removal.
