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ORCIDAttila Cangi
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2020 – today
- 2024
[j4]Attila Cangi
:
Bridging the gap in electronic structure calculations via machine learning. Nat. Comput. Sci. 4(10): 729-730 (2024)- [i4]Karan Shah, Attila Cangi:
Accelerating Electron Dynamics Simulations through Machine Learned Time Propagators. CoRR abs/2407.09628 (2024) - 2023
- [j3]Debanjan Konar, Aditya Das Sarma, Soham Bhandary, Siddhartha Bhattacharyya, Attila Cangi, Vaneet Aggarwal:
A shallow hybrid classical-quantum spiking feedforward neural network for noise-robust image classification. Appl. Soft Comput. 136: 110099 (2023) - [j2]Timothy J. Callow, Jan Nikl, Eli Kraisler, Attila Cangi:
Physics-enhanced neural networks for equation-of-state calculations. Mach. Learn. Sci. Technol. 4(4): 45055 (2023) - [c3]Debanjan Konar, Vaneet Aggarwal, Aditya Das Sarma, Soham Bhandary, Siddhratha Bhattacharyya, Attila Cangi:
Deep Spiking Quantum Neural Network for Noisy Image Classification. IJCNN 2023: 1-10 - [c2]Debanjan Konar, Erol Gelenbe, Soham Bhandary, Aditya Das Sarma, Attila Cangi:
Random Quantum Neural Networks for Noisy Image Recognition. QCE 2023: 276-277 - 2022
- [j1]Lenz Fiedler, Nils Hoffmann, Parvez Mohammed, Gabriel A. Popoola, Tamar Yovell, Vladyslav Oles, J. Austin Ellis, Sivasankaran Rajamanickam, Attila Cangi:
Training-free hyperparameter optimization of neural networks for electronic structures in matter. Mach. Learn. Sci. Technol. 3(4): 45008 (2022) - [c1]Timothy J. Callow, Daniel Kotik, Eli Kraisler, Attila Cangi:
atoMEC: An open-source average-atom Python code. SciPy 2022: 37-45 - [i3]Debanjan Konar, Erol Gelenbe, Soham Bhandary, Aditya Das Sarma, Attila Cangi:
Random Quantum Neural Networks (RQNN) for Noisy Image Recognition. CoRR abs/2203.01764 (2022) - [i2]Dinesh Reddy Vemula, Debanjan Konar, Sudeep Satheesan, Sri Mounica Kalidasu, Attila Cangi:
A Scalable 5, 6-Qubit Grover's Quantum Search Algorithm. CoRR abs/2205.00117 (2022) - 2020
- [i1]J. Austin Ellis, Attila Cangi, Normand A. Modine, J. Adam Stephens, Aidan P. Thompson, Sivasankaran Rajamanickam:
Accelerating Finite-temperature Kohn-Sham Density Functional Theory with Deep Neural Networks. CoRR abs/2010.04905 (2020)
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