581 datasets found

The JARVIS-ML database contains machine learning models for predicting material properties.

The Parameter, Compute and Data Trends in Machine Learning (PCD) database.

The dataset of publications affiliated with the top 25 companies by affiliations with the top-100,000 most cited AI and ML works, and notable ML systems.

The dataset used for building detection using machine learning.

The dataset used in this paper is a multidimensional cascade neural network with neuron pool optimization in each cascade.

Labeled dataset of hotspots/wildfires and not-hotspots/not-wildfires

The dataset used in the paper is a collection of linear regression models with varying dimensions of posterior.

The dataset used in the paper is a stochastic optimal control problem, where the goal is to drive the behavior of a noisy system.

A 3D procedural dataset for X-Ray Computed Tomography and Machine-Learning

The dataset used in this paper for analyzing the memory cost of three machine learning algorithms: transformers, spatial convolution, and FFT.

The dataset used in this paper is a collection of lattice QCD simulations, specifically the three-point correlation function data of nucleon vector and axial-vector charges.

The dataset used in this paper is a collection of high-dimensional observation data from cameras and LiDAR, used for training a world model.

Recent years have seen many successful applications of machine learning (ML) to facilitate fluid dynamic computations. As simulations grow, generating new training datasets for...

The dataset used in this paper is a distributed dataset for learning, where the data is distributed over a trusted network and the communication constraints can create a...

A comprehensive analysis of mammogram images to develop an enhanced understanding of different risk categories associated with breast cancer.

DaCeML is a Data-Centric Machine Learning framework that provides a simple, flexible, and customizable pipeline for optimizing training of arbitrary deep neural networks.

A broad benchmark suite for black-box optimization, covering a wide range of problems, including academic benchmarks, real-world applications, and discrete optimization problems.

The dataset used in the paper is a real-world dataset, specifically the Auto-MPG dataset from the University of California, Irvine (UCI) database.

The EFIGI catalogue by Baillard et al. (2011) is an example of large, pre-processed datasets used to train machine learning models.

Interest in using machine learning for tasks such as galaxy segmentation, and deblending processing, classification, has become popular due to the growth of larger galaxy datasets.