default search action
Sofia Vallecorsa
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
- [j15]Yuri Alexeev, Maximilian Amsler, Marco Antonio Barroca, Sanzio Bassini, Torey Battelle, Daan Camps, David Casanova, Young Jay Choi, Frederic T. Chong, Charles Chung, Christopher Codella, Antonio D. Córcoles, James Cruise, Alberto Di Meglio, Ivan Duran, Thomas Eckl, Sophia E. Economou, Stephan Eidenbenz, Bruce Elmegreen, Clyde Fare, Ismael Faro, Cristina Sanz Fernández, Rodrigo Neumann Barros Ferreira
, Keisuke Fuji, Bryce Fuller, Laura Gagliardi, Giulia Galli, Jennifer R. Glick, Isacco Gobbi, Pranav Gokhale, Salvador de la Puente Gonzalez, Johannes Greiner, Bill Gropp, Michele Grossi, Emanuel Gull, Burns Healy, Matthew R. Hermes
Quantum-centric supercomputing for materials science: A perspective on challenges and future directions. Future Gener. Comput. Syst. 160: 666-710 (2024) - [i30]Cenk Tüysüz, Su Yeon Chang, Maria Demidik, Karl Jansen, Sofia Vallecorsa, Michele Grossi
Symmetry breaking in geometric quantum machine learning in the presence of noise. CoRR abs/2401.10293 (2024) - [i29]Vasilis Belis, Patrick Odagiu, Michele Grossi
Guided Quantum Compression for Higgs Identification. CoRR abs/2402.09524 (2024) - [i28]Carla Rieger, Michele Grossi
Operational Framework for a Quantum Database. CoRR abs/2405.14947 (2024) - 2023
- [j14]Julian Schuhmacher
Unravelling physics beyond the standard model with classical and quantum anomaly detection. Mach. Learn. Sci. Technol. 4(4): 45031 (2023) - [j13]Massimiliano Incudini
Resource saving via ensemble techniques for quantum neural networks. Quantum Mach. Intell. 5(2): 1-24 (2023) - [c18]Su Yeon Chang, Michele Grossi
Approximately Equivariant Quantum Neural Network for p4m Group Symmetries in Images. QCE 2023: 229-235 - [c17]Dominic Pasquali, Michele Grossi
Classification with Integrated Quantum and Spiking Neural Networks. QCE 2023: 298-299 - [c16]Elie Bermot, Christa Zoufal, Michele Grossi
Quantum Generative Adversarial Networks For Anomaly Detection In High Energy Physics. QCE 2023: 331-341 - [i27]Kinga Anna Wozniak, Vasilis Belis, Ema Puljak, Panagiotis Kl. Barkoutsos, Günther Dissertori, Michele Grossi
Quantum anomaly detection in the latent space of proton collision events at the LHC. CoRR abs/2301.10780 (2023) - [i26]Julian Schuhmacher, Laura Boggia, Vasilis Belis, Ema Puljak, Michele Grossi
Unravelling physics beyond the standard model with classical and quantum anomaly detection. CoRR abs/2301.10787 (2023) - [i25]Manuel S. Rudolph, Sacha Lerch, Supanut Thanasilp, Oriel Kiss, Sofia Vallecorsa, Michele Grossi
Trainability barriers and opportunities in quantum generative modeling. CoRR abs/2305.02881 (2023) - [i24]Matteo Biassoni, Andrea Giachero, Michele Grossi
Assessment of few-hits machine learning classification algorithms for low energy physics in liquid argon detectors. CoRR abs/2305.09744 (2023) - [i23]Paulin de Schoulepnikoff, Oriel Kiss, Sofia Vallecorsa, Giuseppe Carleo, Michele Grossi
Hybrid Ground-State Quantum Algorithms based on Neural Schrödinger Forging. CoRR abs/2307.02633 (2023) - [i22]Su Yeon Chang
Approximately Equivariant Quantum Neural Network for p4m Group Symmetries in Images. CoRR abs/2310.02323 (2023) - 2022
- [j12]Marco Rossi
Deep Learning Strategies for ProtoDUNE Raw Data Denoising. Comput. Softw. Big Sci. 6(1) (2022) - [j11]Mario Fernández-Pendás
A study of the performance of classical minimizers in the Quantum Approximate Optimization Algorithm. J. Comput. Appl. Math. 404: 113388 (2022) - [j10]Oriel Kiss
Quantum neural networks force fields generation. Mach. Learn. Sci. Technol. 3(3): 35004 (2022) - [c15]Florian Rehm
Reduced Precision Research of a GAN Image Generation Use-case. ICPRAM (Revised Selected Papers) 2022: 3-22 - [c14]Florian Rehm
Quantum Angle Generator for Image Generation. SEC 2022: 425-429 - [c13]Hongruixuan Chen
Dual-Tasks Siamese Transformer Framework for Building Damage Assessment. IGARSS 2022: 1600-1603 - [c12]Su Yeon Chang
Quantum Convolutional Circuits for Earth Observation Image Classification. IGARSS 2022: 4907-4910 - [i21]Hongruixuan Chen
Dual-Tasks Siamese Transformer Framework for Building Damage Assessment. CoRR abs/2201.10953 (2022) - [i20]Oriel Kiss, Francesco Tacchino, Sofia Vallecorsa, Ivano Tavernelli:
Quantum neural networks force fields generation. CoRR abs/2203.04666 (2022) - [i19]Oriel Kiss, Michele Grossi
Conditional Born machine for Monte Carlo events generation. CoRR abs/2205.07674 (2022) - [i18]Su Yeon Chang, Edwin Agnew, Elías F. Combarro, Michele Grossi
Running the Dual-PQC GAN on noisy simulators and real quantum hardware. CoRR abs/2205.15003 (2022) - [i17]Renato Cardoso, Sofia Vallecorsa, Edoardo Nemni:
Conditional Progressive Generative Adversarial Network for satellite image generation. CoRR abs/2211.15303 (2022) - [i16]Massimiliano Incudini, Michele Grossi
The Quantum Path Kernel: a Generalized Quantum Neural Tangent Kernel for Deep Quantum Machine Learning. CoRR abs/2212.11826 (2022) - 2021
- [j9]Gul Rukh Khattak
High Energy Physics Calorimeter Detector Simulation Using Generative Adversarial Networks With Domain Related Constraints. IEEE Access 9: 108899-108911 (2021) - [j8]Guilherme Amadio, A. Ananya, John Apostolakis, Marilena Bandieramonte, S. Banerjee, Abhijit Bhattacharyya
GeantV. Comput. Softw. Big Sci. 5(1) (2021) - [j7]Wen Guan, Gabriel N. Perdue
Quantum machine learning in high energy physics. Mach. Learn. Sci. Technol. 2(1): 11003 (2021) - [j6]Elías F. Combarro
On a poset of quantum exact promise problems. Quantum Inf. Process. 20(6): 214 (2021) - [j5]Cenk Tüysüz
Hybrid quantum classical graph neural networks for particle track reconstruction. Quantum Mach. Intell. 3(2): 1-20 (2021) - [j4]Elías F. Combarro, Federico Carminati, Sofia Vallecorsa, José Ranilla
On protocols for increasing the uniformity of random bits generated with noisy quantum computers. J. Supercomput. 77(8): 8063-8081 (2021) - [j3]Elías F. Combarro, Sofia Vallecorsa, Luis J. Rodríguez-Muñiz, Álvaro Aguilar-González
A report on teaching a series of online lectures on quantum computing from CERN. J. Supercomput. 77(12): 14405-14435 (2021) - [j2]Elías F. Combarro, Sofia Vallecorsa, Luis J. Rodríguez-Muñiz, Álvaro Aguilar-González, José Ranilla
Correction to: A report on teaching a series of online lectures on quantum computing from CERN. J. Supercomput. 77(12): 14436-14437 (2021) - [c11]Florian Rehm, Sofia Vallecorsa, Kerstin Borras, Dirk Krücker:
Validation of Deep Convolutional Generative Adversarial Networks for High Energy Physics Calorimeter Simulations. AAAI Spring Symposium: MLPS 2021 - [c10]Florian Rehm, Sofia Vallecorsa, Vikram A. Saletore, Hans Pabst, Adel Chaibi, Valeriu Codreanu, Kerstin Borras, Dirk Krücker
Reduced Precision Strategies for Deep Learning: A High Energy Physics Generative Adversarial Network Use Case. ICPRAM 2021: 251-258 - [i15]Su Yeon Chang, Sofia Vallecorsa, Elías F. Combarro, Federico Carminati:
Quantum Generative Adversarial Networks in a Continuous-Variable Architecture to Simulate High Energy Physics Detectors. CoRR abs/2101.11132 (2021) - [i14]Marco Rossi, Sofia Vallecorsa:
Deep Learning strategies for ProtoDUNE raw data denoising. CoRR abs/2103.01596 (2021) - [i13]Agastya P. Bhati, Shunzhou Wan, Dario Alfè, Austin R. Clyde, Mathis Bode, Li Tan, Mikhail Titov, André Merzky, Matteo Turilli, Shantenu Jha, Roger R. Highfield, Walter Rocchia, Nicola Scafuri, Sauro Succi, Dieter Kranzlmüller, Gerald Mathias, David Wifling, Yann Donon, Alberto Di Meglio, Sofia Vallecorsa, Heng Ma, Anda Trifan, Arvind Ramanathan, Tom Brettin, Alexander Partin, Fangfang Xia, Xiaotan Duan, Rick Stevens, Peter V. Coveney:
Pandemic Drugs at Pandemic Speed: Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers. CoRR abs/2103.02843 (2021) - [i12]Florian Rehm, Sofia Vallecorsa, Vikram A. Saletore, Hans Pabst, Adel Chaibi, Valeriu Codreanu, Kerstin Borras, Dirk Krücker:
Reduced Precision Strategies for Deep Learning: A High Energy Physics Generative Adversarial Network Use Case. CoRR abs/2103.10142 (2021) - [i11]Su Yeon Chang, Steven Herbert, Sofia Vallecorsa, Elías F. Combarro, Ross Duncan:
Dual-Parameterized Quantum Circuit GAN Model in High Energy Physics. CoRR abs/2103.15470 (2021) - [i10]Vasileios Belis, Samuel González-Castillo, Christina Reissel, Sofia Vallecorsa, Elías F. Combarro, Günther Dissertori, Florentin Reiter:
Higgs analysis with quantum classifiers. CoRR abs/2104.07692 (2021) - [i9]Florian Rehm, Sofia Vallecorsa, Kerstin Borras, Dirk Krücker:
Physics Validation of Novel Convolutional 2D Architectures for Speeding Up High Energy Physics Simulations. CoRR abs/2105.08960 (2021) - [i8]Joanna Waczynska, Edoardo Martelli, Sofia Vallecorsa, Edward Karavakis, Tony Cass:
Convolutional LSTM models to estimate network traffic. CoRR abs/2107.02496 (2021) - [i7]Cenk Tüysüz, Carla Rieger, Kristiane Novotny, Bilge Demirköz, Daniel Dobos, Karolos Potamianos, Sofia Vallecorsa, Jean-Roch Vlimant, Richard Forster:
Hybrid Quantum Classical Graph Neural Networks for Particle Track Reconstruction. CoRR abs/2109.12636 (2021) - [i6]Renato Cardoso, Dejan Golubovic, Ignacio Peluaga Lozada, Ricardo Rocha, João Fernandes, Sofia Vallecorsa:
Accelerating GAN training using highly parallel hardware on public cloud. CoRR abs/2111.04628 (2021) - 2020
- [c9]John Osorio Ríos, Adrià Armejach, Gulrukh Khattak
Evaluating Mixed-Precision Arithmetic for 3D Generative Adversarial Networks to Simulate High Energy Physics Detectors. ICMLA 2020: 49-56 - [c8]David Brayford
Deploying Scientific Al Networks at Petaflop Scale on Secure Large Scale HPC Production Systems with Containers. PASC 2020: 6:1-6:8 - [i5]David Brayford, Sofia Vallecorsa:
Deploying Scientific AI Networks at Petaflop Scale on Secure Large Scale HPC Production Systems with Containers. CoRR abs/2005.10676 (2020)
2010 – 2019
- 2019
- [c7]David Brayford
Deploying AI Frameworks on Secure HPC Systems with Containers. HPEC 2019: 1-6 - [c6]Gul Rukh Khattak
Particle Detector Simulation using Generative Adversarial Networks with Domain Related Constraints. ICMLA 2019: 28-33 - [c5]Ahmad Hesam, Sofia Vallecorsa, Gulrukh Khattak
Evaluating POWER Architecture for Distributed Training of Generative Adversarial Networks. ISC Workshops 2019: 432-440 - [c4]Chao Jiang
Acceleration of Scientific Deep Learning Models on Heterogeneous Computing Platform with Intel® FPGAs. ISC Workshops 2019: 587-600 - [i4]David Brayford, Sofia Vallecorsa, Atanas Atanasov, Fabio Baruffa, Walter Riviera:
Deploying AI Frameworks on Secure HPC Systems with Containers. CoRR abs/1905.10090 (2019) - [i3]Dawit Belayneh, Federico Carminati, Amir Farbin, Benjamin Hooberman, Gulrukh Khattak, Miaoyuan Liu, Junze Liu, Dominick Olivito, Vitória Barin Pacela, Maurizio Pierini, Alexander G. Schwing, Maria Spiropulu, Sofia Vallecorsa, Jean-Roch Vlimant, Wei Wei, Matt Zhang:
Calorimetry with Deep Learning: Particle Simulation and Reconstruction for Collider Physics. CoRR abs/1912.06794 (2019) - 2018
- [c3]Sofia Vallecorsa, Diana Moise, Federico Carminati, Gul Rukh Khattak
Data-Parallel Training of Generative Adversarial Networks on HPC Systems for HEP Simulations. HiPC 2018: 162-171 - [c2]Gul Rukhkhattak
Three Dimensional Energy Parametrized Generative Adversarial Networks for Electromagnetic Shower Simulation. ICIP 2018: 3913-3917 - [c1]Sofia Vallecorsa, Federico Carminati, Gulrukh Khattak
Distributed Training of Generative Adversarial Networks for Fast Detector Simulation. ISC Workshops 2018: 487-503 - [i2]Kim Albertsson, Piero Altoe, Dustin Anderson, Michael Andrews, Juan Pedro Araque Espinosa, Adam Aurisano
Machine Learning in High Energy Physics Community White Paper. CoRR abs/1807.02876 (2018) - 2015
- [j1]Mark G. Aartsen, Rasha U. Abbasi, Markus Ackermann
The IceProd framework: Distributed data processing for the IceCube neutrino observatory. J. Parallel Distributed Comput. 75: 198-211 (2015) - 2013
- [i1]Mark G. Aartsen, Rasha U. Abbasi, Markus Ackermann, Jenni Adams, Juan Antonio Aguilar Sánchez
The IceProd Framework: Distributed Data Processing for the IceCube Neutrino Observatory. CoRR abs/1311.5904 (2013)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 21:18 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: