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Human-in-the-Loop Interpretability Prior
The dataset used in the paper is a collection of datasets, including synthetic, mushroom, census, and covertype datasets. -
VAEs in the Presence of Missing Data
Real world datasets often contain entries with missing elements e.g. in a medical dataset, a patient is unlikely to have taken all possible diagnostic tests. -
Scientific Machine Learning through Physics-Informed Neural Networks: Where we...
Physics-Informed Neural Networks (PINNs) are a scientific machine learning technique used to solve problems involving Partial Differential Equations (PDEs). -
Training Dataset
The training dataset is a collection of the publicly available Arabic corpora listed below: The unshuffled OSCAR corpus (Ortiz Su´arez et al., 2020). The Arabic Wikipedia dump... -
Test dataset
A dataset of 200 samples with 1283 resolution, generated using VGrain software with a regularity of 0.73 and uniform random orientation -
Compositional Diffusion-Based Continuous Constraint Solvers
The dataset for 2D triangle packing, 2D shape arrangement with qualitative constraints, 3D object stacking with stability constraints, and 3D object packing with robots. -
OpenAI Gym
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used several continuous control environments from the OpenAI Gym. -
Orca: Progressive Learning from Complex Explanation Traces
The Orca approach involves leveraging explanation tuning to generate detailed responses from a large language model. -
Evol-Instruct: A Pipeline for Automatically Evolving Instruction Datasets
The Evol-Instruct pipeline involves automatically evolving instruction datasets using large language models. -
Various Datasets
The datasets used in the paper are described as follows: WikiMIA, BookMIA, Temporal Wiki, Temporal arXiv, ArXiv-1 month, Multi-Webdata, LAION-MI, Gutenberg. -
Compute trends across three eras of machine learning
A dataset of 650 machine learning models presented in academic publications and relevant gray literature. -
Wine Quality Dataset
The dataset used for testing the performance of the proposed LightGCNet-I and LightGCNet-II algorithms on the wine quality dataset. -
A Thermal Machine Learning Solver For Chip Simulation
Thermal analysis provides deeper insights into electronic chips' behavior under different temperature scenarios and enables faster design exploration. However, obtaining... -
Rosenbrock function
The dataset used in the paper is not explicitly mentioned, but it is mentioned that the authors used Rosenbrock function for optimization. -
SimpleQuestion dataset for Wikidata
The dataset used in this paper is a reinforcement learning dataset, specifically the SimpleQuestion dataset, which contains questions answerable using Wikidata as the knowledge... -
CIFAR-10, CIFAR-100, and ImageNet
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used CIFAR-10, CIFAR-100, and ImageNet datasets. -
MNIST Dataset
The MNIST dataset (Lecun et al., 1998), which consists of 60,000 gray-scale images of handwritten digits. Each image has an accompanying label in {0, 1,..., 9}, and is stored as... -
Optimal Binary Autoencoder with Pairwise Correlations
The dataset used in this paper is a binary autoencoder dataset, where the goal is to learn a binary autoencoder that can reconstruct the input data with the worst-case optimal... -
CIFAR-100, MNIST, ImageNet, MIT67, SUN397, Places205
The dataset used in this paper for object recognition on CIFAR-100, MNIST, and ImageNet, and scene recognition on MIT67, SUN397, and Places205.