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Shiba et al. dataset
The dataset used in Shiba et al. 2022, Botan: Bond targeting network for prediction of slow glassy dynamics by machine learning relative motion. -
Bapst et al. dataset
The dataset built by Bapst et al. in It is obtained from molecular dynamics simulations of an 80:20 Kob-Andersen mixture of N = 4096 particles in a three-dimensional box with... -
Implicit Regularization of SGD with Preconditioning for Least Square Problems
The dataset used in the paper is a least squares regression problem instance. -
Next Day Wildfire Spread
A curated, large-scale, multivariate data set of historical wildfires aggregating nearly a decade of remote-sensing data across the United States. -
Simulated dataset
The dataset used in this paper is a simulated dataset with 200 variables and 50 observations. The variables are generated from a multivariate normal distribution with a... -
Chaotic Multiscale System
The dataset is used to test the proposed generalized residue network (gResNet) framework for learning unknown governing equations from observational data. -
Nonlinear ODE Systems
The dataset is used to test the proposed generalized residue network (gResNet) framework for learning unknown governing equations from observational data. -
Linear ODE Systems
The dataset is used to test the proposed generalized residue network (gResNet) framework for learning unknown governing equations from observational data. -
Unknown Dynamical Systems
The dataset is used to test the proposed generalized residue network (gResNet) framework for learning unknown governing equations from observational data. -
Breast Cancer Diagnosis Using Machine Learning Techniques
Breast cancer is one of the most threatening diseases in women’s life; thus, the early and accurate diagnosis plays a key role in reducing the risk of death in a patient’s life.... -
Lit-pcba: an unbiased data set for machine learning and virtual screening
The LIT-PCBA dataset contains experimentally confirmed active and inactive compounds for 15 targets. -
MNIST and CIFAR-10 datasets
The MNIST and CIFAR-10 datasets are used to test the theory suggesting the existence of many saddle points in high-dimensional functions. -
Tree Decay Stages Classification Dataset
The dataset used for training and testing the classification models for tree decay stages from combined airborne LiDAR data and CIR imagery. -
DINOv2: Learning robust visual features without supervision
The authors propose a method for self-supervised representation learning using knowledge distillation and vision transformers. -
Diffusion Classifier
The authors propose a method for zero-shot classification that leverages conditional density estimates from text-to-image diffusion models. -
Diffusion Models Beat GANs on Image Synthesis
Diffusion models have recently emerged as the state-of-the-art of generative modeling, demonstrating remarkable results in image synthesis and across other modalities. -
Diffusion Models and Representation Learning: A Survey
Diffusion Models are popular generative modeling methods in various vision tasks, attracting significant attention. They can be considered a unique instance of self-supervised... -
MISMATCH: Fine-grained Evaluation of Machine-generated Text
The dataset used in the paper for fine-grained evaluation of machine-generated text with mismatch error types.
