Attila Cangi

Orcid: 0000-0001-9162-262X

According to our database1, Attila Cangi authored at least 15 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

2020
2021
2022
2023
2024
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1
2
3
4
5
6
3
2
3
1
2
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1
2

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Bridging the gap in electronic structure calculations via machine learning.
Nat. Comput. Sci., October, 2024

Materials Learning Algorithms (MALA): Scalable Machine Learning for Electronic Structure Calculations in Large-Scale Atomistic Simulations.
CoRR, 2024

Accelerating Electron Dynamics Simulations through Machine Learned Time Propagators.
CoRR, 2024

2023
Physics-enhanced neural networks for equation-of-state calculations.
Mach. Learn. Sci. Technol., December, 2023

A shallow hybrid classical-quantum spiking feedforward neural network for noise-robust image classification.
Appl. Soft Comput., March, 2023

Random Quantum Neural Networks for Noisy Image Recognition.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

Deep Spiking Quantum Neural Network for Noisy Image Classification.
Proceedings of the International Joint Conference on Neural Networks, 2023

2022
Training-free hyperparameter optimization of neural networks for electronic structures in matter.
Mach. Learn. Sci. Technol., December, 2022

Scripts and Models for "Predicting electronic structures at any length scale with machine learning".
Dataset, September, 2022

A Scalable 5, 6-Qubit Grover's Quantum Search Algorithm.
CoRR, 2022

Random Quantum Neural Networks (RQNN) for Noisy Image Recognition.
CoRR, 2022

atoMEC: An open-source average-atom Python code.
Proceedings of the 21st Python in Science Conference 2022, 2022

2021
Dataset and scripts for A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry.
Dataset, October, 2021

Dataset and scripts for A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry.
Dataset, October, 2021

2020
Accelerating Finite-temperature Kohn-Sham Density Functional Theory with Deep Neural Networks.
CoRR, 2020


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