194 datasets found

This dataset contains the pretrained baseline models, namely FNO, U-Net, and PINN. These models are trained on different PDEs, such as 1D advection, 1D Burgers', 1D and 2D...

Data for the publication High-accuracy thermodynamic properties to the melting point from ab initio calculations aided by machine-learning potentials, npj Comput. Mater., DOI:...

This dataset contains diffusion-sorption data, generated with numerical simulation based on three different sorption isotherms, namely the linear, Freundlich, and Langmuir...

Data for the publication Thermodynamic properties on the homologous temperature scale from direct upsampling: Understanding electron-vibration coupling and thermal vacancies in...

We propose Unified Model of Saliency and Scanpaths (UMSS) - a model that learns to predict multi-duration saliency and scanpaths (i.e. sequences of eye fixations) on information...

Supplemental material for the poster "Visual-Explainable AI: The Use Case of Language Models" published at the International Conference on Data-Integrated Simulation Science...

Data for the publication "Performance of two complementary machine-learned potentials in modelling chemically complex systems", npj. Comp. Mat. This data set contains the...

This dataverse contains the code for the paper Meta-Uncertainty in Bayesian Model Comparison: https://doi.org/10.48550/arXiv.2210.07278 Note that the R code is structured as a...

Data for the publication, Dynamically stabilized phases with full ab initio accuracy: Thermodynamics of Ti, Zr, Hf with a focus on the hcp-bcc transition, Phys. Rev. B 108,...

This dataset contains all experimental data that is shown within the paper "Learning Compensation of the State-Dependent Transmission Errors in Rack-and-Pinion Drives"....

Data sets of the article "Constraint-aware neural networks for Riemann problems", consisting of training and test data sets for Riemann solutions of the cubic flux model, an...

The datasets and codes provided here are associated with our article entitled "Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a...

Data for "Srinivasan, P., Demuriya, D., Grabowski, B. et al. Electronic Moment Tensor Potentials include both electronic and vibrational degrees of freedom. npj Comput Mater 10,...

This code is a PyTorch implementation of the paper "NestE: Modeling Nested Relational Structures for Knowledge Graph Reasoning (AAAI'24)". NestE is a knowledge graph embedding...

This is a Pytorch implementation of the paper Shrinking Embeddings for Hyper-relational Knowledge Graphs published in ACL'23. This code is used to reproduce the experiments of...

This code allows to replicate key experiments from our paper: Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference. For further details, please...

This dataset contains the necessary code for using our spray segmentation model used in the paper, Machine learning based spray process quantification. More information can be...

This dataset includes the code to reproduce the results from the paper titled "Greedy Kernel Methods for Approximating Breakthrough Curves for Reactive Flow from 3D Porous...

Replication Data for: SCAP 2024 Robotic Wiring Harness Bin Picking. 4K Images from 3 Camera Perspectives including Annotation data for Reproduction of the Learning for the ML...

This dataset is the official implementation of Pseudo-Riemannian Graph Convolutional Networks in PyTorch, based on HGCN implementation. This code is used to reproduce the...