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Attila Cangi
ORCID
Publication Activity (10 Years)
Years Active: 2020-2024
Publications (10 Years): 10
Top Topics
Quantum Computing
Neural Network
Image Recognition
Grid Search
Top Venues
CoRR
Mach. Learn. Sci. Technol.
QCE
SciPy
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Publications
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Karan Shah
,
Attila Cangi
Accelerating Electron Dynamics Simulations through Machine Learned Time Propagators.
CoRR
(2024)
Debanjan Konar
,
Erol Gelenbe
,
Soham Bhandary
,
Aditya Das Sarma
,
Attila Cangi
Random Quantum Neural Networks for Noisy Image Recognition.
QCE
(2023)
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 (2023)
Debanjan Konar
,
Vaneet Aggarwal
,
Aditya Das Sarma
,
Soham Bhandary
,
Siddhratha Bhattacharyya
,
Attila Cangi
Deep Spiking Quantum Neural Network for Noisy Image Classification.
IJCNN
(2023)
Timothy J. Callow
,
Jan Nikl
,
Eli Kraisler
,
Attila Cangi
Physics-enhanced neural networks for equation-of-state calculations.
Mach. Learn. Sci. Technol.
4 (4) (2023)
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) (2022)
Debanjan Konar
,
Erol Gelenbe
,
Soham Bhandary
,
Aditya Das Sarma
,
Attila Cangi
Random Quantum Neural Networks (RQNN) for Noisy Image Recognition.
CoRR
(2022)
Timothy J. Callow
,
Daniel Kotik
,
Eli Kraisler
,
Attila Cangi
atoMEC: An open-source average-atom Python code.
SciPy
(2022)
Dinesh Reddy Vemula
,
Debanjan Konar
,
Sudeep Satheesan
,
Sri Mounica Kalidasu
,
Attila Cangi
A Scalable 5, 6-Qubit Grover's Quantum Search Algorithm.
CoRR
(2022)
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
(2020)