Accelerating Finite-temperature Kohn-Sham Density Functional Theory with Deep Neural Networks. - J. Austin Ellis; Attila Cangi; Normand A. Modine; J. Adam Stephens; Aidan P. Thompson; Sivasankaran Rajamanickam (CoRR, 2020)

Dataset and scripts for A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry. - Lenz Fiedler; Karan Shah 001; Attila Cangi; Michael Bussmann (RODARE, 2021)

Dataset and scripts for A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry. - Lenz Fiedler; Karan Shah 001; Attila Cangi; Michael Bussmann (RODARE, 2021)

atoMEC: An open-source average-atom Python code. - Timothy J. Callow; Daniel Kotik; Eli Kraisler; Attila Cangi (SciPy, 2022)

Random Quantum Neural Networks (RQNN) for Noisy Image Recognition. - Debanjan Konar; Erol Gelenbe; Soham Bhandary; Aditya Das Sarma; Attila Cangi (CoRR, 2022)

A Scalable 5, 6-Qubit Grover's Quantum Search Algorithm. - Dinesh Reddy Vemula; Debanjan Konar; Sudeep Satheesan; Sri Mounica Kalidasu; Attila Cangi (CoRR, 2022)

Scripts and Models for "Predicting electronic structures at any length scale with machine learning". - Lenz Fiedler; Steve Schmerler; Normand A. Modine; Dayton J. Vogel; Gabriel A. Popoola; Aidan P. Thompson; Sivasankaran Rajamanickam; Attila Cangi (RODARE, 2022)

Training-free hyperparameter optimization of neural networks for electronic structures in matter. - Lenz Fiedler; Nils Hoffmann; Parvez Mohammed; Gabriel A. Popoola; Tamar Yovell; Vladyslav Oles; J. Austin Ellis; Sivasankaran Rajamanickam; Attila Cangi (Mach. Learn. Sci. Technol., 2022)

Deep Spiking Quantum Neural Network for Noisy Image Classification. - Debanjan Konar; Vaneet Aggarwal; Aditya Das Sarma; Soham Bhandary; Siddhratha Bhattacharyya; Attila Cangi (IJCNN, 2023)

Random Quantum Neural Networks for Noisy Image Recognition. - Debanjan Konar; Erol Gelenbe; Soham Bhandary; Aditya Das Sarma; Attila Cangi (QCE, 2023)

A shallow hybrid classical-quantum spiking feedforward neural network for noise-robust image classification. - Debanjan Konar; Aditya Das Sarma; Soham Bhandary; Siddhartha Bhattacharyya; Attila Cangi; Vaneet Aggarwal (Appl. Soft Comput., 2023)

Physics-enhanced neural networks for equation-of-state calculations. - Timothy J. Callow; Jan Nikl; Eli Kraisler; Attila Cangi (Mach. Learn. Sci. Technol., 2023)

Accelerating Electron Dynamics Simulations through Machine Learned Time Propagators. - Karan Shah 001; Attila Cangi (CoRR, 2024)

Bridging the gap in electronic structure calculations via machine learning. - Attila Cangi (Nat. Comput. Sci., 2024)

Materials Learning Algorithms (MALA): Scalable machine learning for electronic structure calculations in large-scale atomistic simulations. - Attila Cangi; Lenz Fiedler; Bartosz Brzoza; Karan Shah 001; Timothy J. Callow; Daniel Kotik; Steve Schmerler; Matthew C. Barry; James M. Goff; Andrew Rohskopf; Dayton J. Vogel; Normand A. Modine; et al. (Comput. Phys. Commun., 2025)