QTML 2023: 7TH INTERNATIONAL CONFERENCE ON QUANTUM TECHINQUES IN MACHINE LEARNING

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Abbas, Amira	On quantum backpropagation, information reuse, and cheating measurement collapse
Acar, Ozan	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Akbari Asanjan, Ata	Hybrid quantum-classical reservoir computing for solving chaotic systems
Albrecht, Boris	Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor
Allcock, Jon	Constant-depth circuits for Uniformly Controlled Gates and Boolean functions with application to quantum memory circuits
Amini, Nina	Quantum Distance Calculation for ε-Graph Construction
Aolita, Leandro	Complete quantum-inspired framework for simulations of flows past immersed bodies
Araujo, Israel F.	Neural Quantum Embedding: Pushing the Limits of Quantum Supervised Learning
Argentieri, Henrique	Complete quantum-inspired framework for simulations of flows past immersed bodies
Arvind, Rahul	Homogenous space expressibility of parametrized quantum circuits
Au, Thi Huong	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
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Baert, Aurelien	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Bai, Ge	Quantum Similarity Testing with Convolutional Neural Networks
Bao, Jinge	Constant-depth circuits for Uniformly Controlled Gates and Boolean functions with application to quantum memory circuits
Barkoutsos, Panagiotis	Quantum anomaly detection in the latent space of proton collision events at the LHC
Bassi, Angelo	QResNet: a variational entanglement skipping algorithm
Belabas, Nadia	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Belis, Vasilis	Quantum anomaly detection in the latent space of proton collision events at the LHC
Benedetti, Marcello	On the Sample Complexity of Quantum Boltzmann Machine Learning
Berberich, Julian	Training robust quantum classifiers based on Lipschitz bounds
Bertasi, Eric	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Bharti, Kishor	Homogenous space expressibility of parametrized quantum circuits
Biamonte, Jacob	On The Performance And Limitation Of Quantum Approximate Optimization
Bilkis, Matias	Machine learning continuously monitored systems: estimating parameters
Billard, Marie	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Blank, Carsten	Hierarchical quantum circuit representations for neural architecture search
Blekos, Kostas	Performance Analysis and Comparative Study of Quantum Approximate Optimization Algorithm Variants
Boissier, Sebastien	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Bonet-Monroig, Xavier	Analyzing variational quantum landscapes with information content
Braccia, Paolo	Equivariant Quantum Models
Brand, Dean	Performance Analysis and Comparative Study of Quantum Approximate Optimization Algorithm Variants
Bravo-Prieto, Carlos	Understanding quantum machine learning also requires rethinking generalization
Brieussel, Alexandre	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Bukov, Marin	Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks
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Calsamiglia, John	Machine learning continuously monitored systems: estimating parameters
Campos, Ernesto	On The Performance And Limitation Of Quantum Approximate Optimization
Cao, Changsu	Ab initio Quantum Simulation of Strongly Correlated Materials with Quantum Embedding
Carleo, Giuseppe	Variational Quantum Time Evolution without the Quantum Geometric Tensor Simulating dynamics of large quantum systems on small quantum devices using circuit knitting
Caro, Matthias C.	Classical Verification of Quantum Learning The power and limitations of learning quantum dynamics incoherently
Carrasquilla, Juan	Here comes the SU(N) multivariate quantum gates and gradients Quantum optimization of Binary Neural Networks
Cerezo, Marco	The landscape of QAOA Max-Cut Lie algebras Equivariant Quantum Models Deep quantum neural networks form Gaussian processes
Ceschini, Andrea	A General Approach for Dropout in Quantum Neural Networks Performance Analysis and Comparative Study of Quantum Approximate Optimization Algorithm Variants
Chang, Su Yeon	Approximately Equivariant Quantum Neural Network for p4m Group Symmetries in Images
Chen, Yifei	Efficient information recovery from Pauli noise via classical shadow
Chinzei, Koki	Splitting and Parallelizing of Quantum Convolutional Neural Networks for Learning Translationally Symmetric Data
Chiribella, Giulio	Quantum Similarity Testing with Convolutional Neural Networks
Chmielewski, Naomi Mona	Quantum Distance Calculation for ε-Graph Construction
Chotibut, Thiparat	Next Generation Quantum Reservoir Computing: An Efficient Quantum Algorithm for Forecasting Quantum Dynamics
Chou, Chiao-Hui	Performance Analysis and Comparative Study of Quantum Approximate Optimization Algorithm Variants
Cline, Julia	Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor
Coish, William A.	Neural–Shadow Quantum State Tomography
Coles, Patrick	The landscape of QAOA Max-Cut Lie algebras The power and limitations of learning quantum dynamics incoherently
Collura, Mario	Quantum optimization of Binary Neural Networks
Coopmans, Luuk	On the Sample Complexity of Quantum Boltzmann Machine Learning
Creevey, Floyd	Quantum machine learning with enhanced adversarial robustness
Crognaletti, Giulio	QResNet: a variational entanglement skipping algorithm
Cîrstoiu, Cristina	Classical simulations of noisy variational quantum circuits
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D'Arcangelo, Mauro	Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor
Dahlsten, Oscar	Dimension reduction in quantum stochastic modelling
Dalyac, Constantin	Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor
Dangniam, Ninnat	Next Generation Quantum Reservoir Computing: An Efficient Quantum Algorithm for Forecasting Quantum Dynamics
Di Pierro, Alessandra	A Topological Features Based Quantum Kernel
Dissertori, Günther	Quantum anomaly detection in the latent space of proton collision events at the LHC
Djellabi, Mehdi	Extending Graph Transformers with Quantum Computed Aggregation
Doriguello, João	Constant-depth circuits for Uniformly Controlled Gates and Boolean functions with application to quantum memory circuits Quantum algorithm for robust optimization via stochastic-gradient online learning
Du, Yuxuan	Demystify Problem-Dependent Power of Quantum Neural Networks on Multi-Class Classification Transition role of entangled data in quantum machine learning
Duncan, Ross	Classical simulations of noisy variational quantum circuits
Dunjko, Vedran	Shadows of quantum machine learning Exponential separations between classical and quantum learners
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Eisert, Jens	Understanding quantum machine learning also requires rethinking generalization
Elfving, Vincent E	Let Quantum Neural Networks Choose Their Own Frequencies Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor
Elliott, Thomas	Quantum adaptive agents with efficient long-term memories Dimension reduction in quantum stochastic modelling
Emeriau, Pierre-Emmanuel	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Erfani, Sarah	Quantum machine learning with enhanced adversarial robustness
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Farinati, Marco	The landscape of QAOA Max-Cut Lie algebras
Fink, Daniel	Training robust quantum classifiers based on Lipschitz bounds
Fioretto, Dario	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Fontana, Enrico	Classical simulations of noisy variational quantum circuits
Fouilland, Romain	Extending Graph Transformers with Quantum Computed Aggregation
Frohnert, Felix	Explainable Representation Learning of Small Quantum States
Fyrillas, Andreas	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
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G. Angelakis, Dimitris	Expressivity and Generalization Ability of Trace-induced Quantum Kernels
Gacon, Julien	Variational Quantum Time Evolution without the Quantum Geometric Tensor
Gan, Beng Yee	Expressivity and Generalization Ability of Trace-induced Quantum Kernels
García-Martín, Diego	Deep quantum neural networks form Gaussian processes
Garner, Andrew	Dimension reduction in quantum stochastic modelling
Garner, Andrew	Quantum adaptive agents with efficient long-term memories
Gasbarri, Giulio	Machine learning continuously monitored systems: estimating parameters
Geaney, Shaun	Hybrid quantum-classical reservoir computing for solving chaotic systems
Gentile, Antonio A	Let Quantum Neural Networks Choose Their Own Frequencies
Gentinetta, Gian	Simulating dynamics of large quantum systems on small quantum devices using circuit knitting
Gerace, Dario	A General Approach for Dropout in Quantum Neural Networks
Gibbs, Joe	The power and limitations of learning quantum dynamics incoherently
Gil-Fuster, Elies	Understanding quantum machine learning also requires rethinking generalization
Gilboa, Dar	On quantum backpropagation, information reuse, and cheating measurement collapse
Giorgi, Gian Luca	Time-series quantum reservoir computing with weak and projective measurements
Grossi, Michele	QResNet: a variational entanglement skipping algorithm Approximately Equivariant Quantum Neural Network for p4m Group Symmetries in Images Trainability barriers and opportunities in quantum generative modeling Quantum anomaly detection in the latent space of proton collision events at the LHC Detection of quantum phase transitions with quantum machine learning techniques
Gu, Mile	Dimension reduction in quantum stochastic modelling
Gu, Mile	Quantum adaptive agents with efficient long-term memories
Guo, Guang-Can	Dimension reduction in quantum stochastic modelling
Gyurik, Casper	Shadows of quantum machine learning Exponential separations between classical and quantum learners
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Hamma, Alioscia	Learning t-doped stabilizer states
Haug, Tobias	Understanding generalization with quantum geometry
He, Ren-Dong	Dimension reduction in quantum stochastic modelling
Hease, William	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Henriet, Loic	Extending Graph Transformers with Quantum Computed Aggregation
Henriet, Loic	Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor
Henry, Louis-Paul	Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor
Heredge, Jamie	Quantum machine learning with enhanced adversarial robustness
Hinsche, Marcel	Classical Verification of Quantum Learning
Hollenberg, Lloyd	Quantum machine learning with enhanced adversarial robustness
Holm, Christian	Training robust quantum classifiers based on Lipschitz bounds
Holmes, Zoë	Trainability barriers and opportunities in quantum generative modeling The power and limitations of learning quantum dynamics incoherently
Hsieh, Min-hsiu	Demystify Problem-Dependent Power of Quantum Neural Networks on Multi-Class Classification
Hu, Hanshi	Ab initio Quantum Simulation of Strongly Correlated Materials with Quantum Embedding
Huang, Hsin-Yuan	On quantum backpropagation, information reuse, and cheating measurement collapse The power and limitations of learning quantum dynamics incoherently
Huang, Po-Wei	Post-Variational Quantum Neural Networks
Huang, Yifei	Quantum Computing Quantum Monte Carlo
Huggins, William J	On quantum backpropagation, information reuse, and cheating measurement collapse Quantum models and data through a precomputation lens
Hur, Tak	Neural Quantum Embedding: Pushing the Limits of Quantum Supervised Learning
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Inack, Estelle	Quantum optimization of Binary Neural Networks
Incudini, Massimiliano	A Topological Features Based Quantum Kernel
Ioannou, Marios	Classical Verification of Quantum Learning
Irwin Jordan, Michael	Quadratic Speedup in Quantum Zero-Sum Games via Single-Call Mirror-Prox Matrix Methods
Ivanov, Edouard	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
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Jacquot, Paulin	Quantum Distance Calculation for ε-Graph Construction
Jaderberg, Ben	Let Quantum Neural Networks Choose Their Own Frequencies
Jain, Nishant	Quantum Fourier Networks for Solving Parametric PDEs
Jembere, Edgar	A Multi-Class Quantum Kernel-Based Classifier
Jerbi, Sofiene	Shadows of quantum machine learning The power and limitations of learning quantum dynamics incoherently
Jung, Johannes	Applying Genetic Algorithms to Optimize the Generalization Ability of Variational Quantum Circuits
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Kazi, Sujay	The landscape of QAOA Max-Cut Lie algebras
Kerenidis, Iordanis	Quantum Fourier Networks for Solving Parametric PDEs
Khoo, Jun Yong	Homogenous space expressibility of parametrized quantum circuits
Killoran, Nathan	Here comes the SU(N) multivariate quantum gates and gradients
Kim, M.S.	Understanding generalization with quantum geometry
King, Robbie	On quantum backpropagation, information reuse, and cheating measurement collapse
Kiss, Oriel	Symmetry-invariant quantum machine learning force fields Detection of quantum phase transitions with quantum machine learning techniques
Kiss, Oriel	Trainability barriers and opportunities in quantum generative modeling
Koh, Dax Enshan	Homogenous space expressibility of parametrized quantum circuits
Kong, Jian Feng	Homogenous space expressibility of parametrized quantum circuits
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Lami, Guglielmo	Quantum optimization of Binary Neural Networks
Landman, Jonas	Quantum Fourier Networks for Solving Parametric PDEs
Larocca, Martin	The landscape of QAOA Max-Cut Lie algebras Equivariant Quantum Models Deep quantum neural networks form Gaussian processes
Lassablière, Lucas	Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor
Le, Isabel Nha Minh	Symmetry-invariant quantum machine learning force fields
Le Saux, Bertrand	Approximately Equivariant Quantum Neural Network for p4m Group Symmetries in Images
Leckie, Christopher	Quantum machine learning with enhanced adversarial robustness
Leclerc, Lucas	Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor
Leone, Lorenzo	Learning t-doped stabilizer states
Lerch, Sacha	Trainability barriers and opportunities in quantum generative modeling
Letcher, Alistair	On the Absence of Barren Plateaus in Quantum Generative Adversarial Networks
Lewis, Dylan	Here comes the SU(N) multivariate quantum gates and gradients
Leykam, Daniel	Expressivity and Generalization Ability of Trace-induced Quantum Kernels
Li, Chuan-Feng	Dimension reduction in quantum stochastic modelling
Li, Rui-Hao	Performance Analysis and Comparative Study of Quantum Approximate Optimization Algorithm Variants
Lim, Debbie Huey Chih	Quantum algorithm for robust optimization via stochastic-gradient online learning
Liu, Feiyang	Dimension reduction in quantum stochastic modelling
Llinas, Marta Florida	Dimension reduction in quantum stochastic modelling
Lott, Aaron	Hybrid quantum-classical reservoir computing for solving chaotic systems
Lott, Philippe	Complete quantum-inspired framework for simulations of flows past immersed bodies
Lourens, Matt	Hierarchical quantum circuit representations for neural architecture search
Luo, Yong	Transition role of entangled data in quantum machine learning
Luongo, Alessandro	Constant-depth circuits for Uniformly Controlled Gates and Boolean functions with application to quantum memory circuits
Lv, Dingshun	Quantum Computing Quantum Monte Carlo Ab initio Quantum Simulation of Strongly Correlated Materials with Quantum Embedding
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Macchiavello, Chiara	Channel tomography for quantum noise characterization and mitigation
Maccone, Lorenzo	Channel tomography for quantum noise characterization and mitigation
Mandarino, Antonio	Detection of quantum phase transitions with quantum machine learning techniques
Mansfield, Shane	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Margaria, Nico	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Maring, Nicolas	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Marini, Alessandro	Complete quantum-inspired framework for simulations of flows past immersed bodies
Marshall, Simon	Shadows of quantum machine learning
Martini, Francesco	A Topological Features Based Quantum Kernel
Martyniuk, Darya	Applying Genetic Algorithms to Optimize the Generalization Ability of Variational Quantum Circuits
Martínez-Peña, Rodrigo	Time-series quantum reservoir computing with weak and projective measurements
Maruyama, Kazunori	Splitting and Parallelizing of Quantum Convolutional Neural Networks for Learning Translationally Symmetric Data
Mathur, Natansh	Quantum Fourier Networks for Solving Parametric PDEs
McClean, Jarrod	On quantum backpropagation, information reuse, and cheating measurement collapse Quantum models and data through a precomputation lens
Mertikopoulos, Panayotis	Quadratic Speedup in Quantum Zero-Sum Games via Single-Call Mirror-Prox Matrix Methods
Metz, Friederike	Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks
Metz, Friederike	Simulating dynamics of large quantum systems on small quantum devices using circuit knitting
Mezher, Rawad	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Miessen, Alexander	Quantum data learning for quantum simulations in high-energy physics
Mikael, Joseph	Quantum Distance Calculation for ε-Graph Construction
Miyamoto, Koichi	Quantum Metropolis-Hastings algorithm with the target distribution calculated by quantum Monte Carlo integration
Molteni, Riccardo	Shadows of quantum machine learning
Motamedi, Arsalan	Gibbs Sampling of Periodic Potentials on a Quantum Computer
Movassagh, Ramis	On quantum backpropagation, information reuse, and cheating measurement collapse
Mujal, Pere	Time-series quantum reservoir computing with weak and projective measurements
Muschik, Christine	Neural–Shadow Quantum State Tomography
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Nagano, Lento	Quantum data learning for quantum simulations in high-energy physics
Nakhl, Chris	Quantum machine learning with enhanced adversarial robustness
Nguyen, Quynh	Equivariant Quantum Models
Nietner, Alexander	Classical Verification of Quantum Learning
Nys, Jannes	Variational Quantum Time Evolution without the Quantum Geometric Tensor
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O'Connor, Daniel	Hybrid quantum-classical reservoir computing for solving chaotic systems
Oliviero, Salvatore Francesco Emanuele	Learning t-doped stabilizer states
Onodera, Tamiya	Quantum data learning for quantum simulations in high-energy physics
Ortiz-Guttiérez, Luis	Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor
Oshima, Hirotaka	Splitting and Parallelizing of Quantum Convolutional Neural Networks for Learning Translationally Symmetric Data
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Pandya, Komal	Performance Analysis and Comparative Study of Quantum Approximate Optimization Algorithm Variants
Panella, Massimo	A General Approach for Dropout in Quantum Neural Networks
Park, Daniel	Hierarchical quantum circuit representations for neural architecture search Neural Quantum Embedding: Pushing the Limits of Quantum Supervised Learning
Paschke, Adrian	Applying Genetic Algorithms to Optimize the Generalization Ability of Variational Quantum Circuits
Peddinti, Raghavendra	Complete quantum-inspired framework for simulations of flows past immersed bodies
Peters, Evan	Learning bounds and guarantees for testing (quantum) hypotheses
Petruccione, Francesco	Hierarchical quantum circuit representations for neural architecture search A Multi-Class Quantum Kernel-Based Classifier
Pham, Hung Q.	Ab initio Quantum Simulation of Strongly Correlated Materials with Quantum Embedding
Pierini, Maurizio	Quantum anomaly detection in the latent space of proton collision events at the LHC
Piliouras, Georgios	Quadratic Speedup in Quantum Zero-Sum Games via Single-Call Mirror-Prox Matrix Methods
Pillay, Shivani	A Multi-Class Quantum Kernel-Based Classifier
Pishchagin, Anton	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Pisoni, Stefano	Complete quantum-inspired framework for simulations of flows past immersed bodies
Pont, Mathias	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Pranjic, Daniel	Training robust quantum classifiers based on Lipschitz bounds
Puljak, Ema	Quantum anomaly detection in the latent space of proton collision events at the LHC
Pérez-Salinas, Adrián	Analyzing variational quantum landscapes with information content
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Rabinovich, Daniil	On The Performance And Limitation Of Quantum Approximate Optimization
Ragone, Michael	Equivariant Quantum Models
Rebentrost, Patrick	Post-Variational Quantum Neural Networks Quantum algorithm for robust optimization via stochastic-gradient online learning
Reiter, Florentin	Quantum anomaly detection in the latent space of proton collision events at the LHC
Rinaldi, Enrico	Deep Learning of Quantum Correlations for Quantum Parameter Estimation of Continuously Monitored Systems
Ronagh, Pooya	Neural–Shadow Quantum State Tomography Gibbs Sampling of Periodic Potentials on a Quantum Computer
Roncallo, Simone	Channel tomography for quantum noise characterization and mitigation
Rossi, Riccardo	Variational Quantum Time Evolution without the Quantum Geometric Tensor
Rudolph, Manuel Sebastian	Classical simulations of noisy variational quantum circuits Trainability barriers and opportunities in quantum generative modeling The power and limitations of learning quantum dynamics incoherently
Rungger, Ivan	Classical simulations of noisy variational quantum circuits
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Salavrakos, Alexia	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Sanchez Munos, Carlos	Deep Learning of Quantum Correlations for Quantum Parameter Estimation of Continuously Monitored Systems
Santha, Miklos	Constant-depth circuits for Uniformly Controlled Gates and Boolean functions with application to quantum memory circuits
Sato, Shintaro	Splitting and Parallelizing of Quantum Convolutional Neural Networks for Learning Translationally Symmetric Data
Sauvage, Frederic	Equivariant Quantum Models
Scala, Francesco	A General Approach for Dropout in Quantum Neural Networks
Schatzki, Louis	Equivariant Quantum Models
Schuhmacher, Julian	Symmetry-invariant quantum machine learning force fields
Senellart, Jean	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Senellart, Pascale	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Sevior, Martin	Quantum machine learning with enhanced adversarial robustness
Signoles, Adrien	Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor
Silvério, Henrique	Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor
Sinayskiy, Ilya	Hierarchical quantum circuit representations for neural architecture search A Multi-Class Quantum Kernel-Based Classifier
Sinnott, Patrick	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Somaschi, Niccolo	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Soriano, Miguel C.	Time-series quantum reservoir computing with weak and projective measurements
Sornsaeng, Apimuk	Next Generation Quantum Reservoir Computing: An Efficient Quantum Algorithm for Forecasting Quantum Dynamics
Stepanov, Petr	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
Strbac, Elena	Hybrid quantum-classical reservoir computing for solving chaotic systems
Summer, Alessandro	Performance Analysis and Comparative Study of Quantum Approximate Optimization Algorithm Variants
Sun, Jinzhao	Quantum Computing Quantum Monte Carlo Ab initio Quantum Simulation of Strongly Correlated Materials with Quantum Embedding
Sweke, Ryan	Classical Verification of Quantum Learning
Sünkel, Leo	Applying Genetic Algorithms to Optimize the Generalization Ability of Variational Quantum Circuits
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Tacchino, Francesco	Symmetry-invariant quantum machine learning force fields Quantum data learning for quantum simulations in high-energy physics
Tao, Dacheng	Demystify Problem-Dependent Power of Quantum Neural Networks on Multi-Class Classification
Tao, Dacheng	Transition role of entangled data in quantum machine learning
Tavernelli, Ivano	Symmetry-invariant quantum machine learning force fields Quantum anomaly detection in the latent space of proton collision events at the LHC Quantum data learning for quantum simulations in high-energy physics
Terashi, Koji	Quantum data learning for quantum simulations in high-energy physics
Thabet, Slimane	Extending Graph Transformers with Quantum Computed Aggregation Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor
Thanasilp, Supanut	Expressivity and Generalization Ability of Trace-induced Quantum Kernels Trainability barriers and opportunities in quantum generative modeling
Thompson, Jayne	Dimension reduction in quantum stochastic modelling
Thompson, Jayne	Quantum adaptive agents with efficient long-term memories
Tischler, Nora	Dimension reduction in quantum stochastic modelling
Tiunov, Egor	Complete quantum-inspired framework for simulations of flows past immersed bodies
Torta, Pietro	Quantum optimization of Binary Neural Networks
Tran, Quoc Hoan	Splitting and Parallelizing of Quantum Convolutional Neural Networks for Learning Translationally Symmetric Data
Tu, Zhuozhuo	Transition role of entangled data in quantum machine learning
Tutschku, Christian	Training robust quantum classifiers based on Lipschitz bounds
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Usman, Muhammad	Quantum machine learning with enhanced adversarial robustness
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Vallecorsa, Sofia	QResNet: a variational entanglement skipping algorithm Approximately Equivariant Quantum Neural Network for p4m Group Symmetries in Images Trainability barriers and opportunities in quantum generative modeling Quantum anomaly detection in the latent space of proton collision events at the LHC
Valvidia, Mario	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
van Nieuwenburg, Evert	Explainable Representation Learning of Small Quantum States
Vasconcelos, Francisca	Quadratic Speedup in Quantum Zero-Sum Games via Single-Call Mirror-Prox Matrix Methods
Venturelli, Davide	Hybrid quantum-classical reservoir computing for solving chaotic systems
Vishwanathan, Akshay	On The Performance And Limitation Of Quantum Approximate Optimization
Vlatakis Gkaragkounis, Emmanouil Vasileios	Quadratic Speedup in Quantum Zero-Sum Games via Single-Call Mirror-Prox Matrix Methods
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Wang, Hao	Analyzing variational quantum landscapes with information content
Wang, Xin	Efficient information recovery from Pauli noise via classical shadow
Wang, Xinbiao	Transition role of entangled data in quantum machine learning
Wang, Yuexuan	Quantum Similarity Testing with Convolutional Neural Networks
Wei, Victor	Neural–Shadow Quantum State Tomography
Wein, Stephen	Variational quantum algorithms implemented on a general-purpose single-photon-based quantum computing platform
West, Maxwell	Quantum machine learning with enhanced adversarial robustness
Wierichs, David	Here comes the SU(N) multivariate quantum gates and gradients
Wiersema, Roeland	Here comes the SU(N) multivariate quantum gates and gradients
Wilson, Max	Hybrid quantum-classical reservoir computing for solving chaotic systems
Woerner, Stefan	Variational Quantum Time Evolution without the Quantum Geometric Tensor On the Absence of Barren Plateaus in Quantum Generative Adversarial Networks
Wozniak, Kinga Anna	Quantum anomaly detection in the latent space of proton collision events at the LHC
Wu, Kang-da	Dimension reduction in quantum stochastic modelling
Wu, Yadong	Quantum Similarity Testing with Convolutional Neural Networks
Wudarski, Filip	Hybrid quantum-classical reservoir computing for solving chaotic systems
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Xiang, Guo-Yong	Dimension reduction in quantum stochastic modelling
Ximenez, Bruno	Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor
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Yang, Chengran	Dimension reduction in quantum stochastic modelling
Yang, Yibo	Demystify Problem-Dependent Power of Quantum Neural Networks on Multi-Class Classification
Yu, Zhan	Efficient information recovery from Pauli noise via classical shadow
Yuan, Xiao	Quantum Computing Quantum Monte Carlo Ab initio Quantum Simulation of Strongly Correlated Materials with Quantum Embedding Transition role of entangled data in quantum machine learning
Yung, Man Hong	Dimension reduction in quantum stochastic modelling
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Zambrini, Roberta	Time-series quantum reservoir computing with weak and projective measurements
Zeier, Robert	The landscape of QAOA Max-Cut Lie algebras
Zhang, Yukun	Quantum Computing Quantum Monte Carlo
Zhao, Haimeng	Non-IID Quantum Federated Learning with One-shot Communication Complexity
Zhu, Chenghong	Efficient information recovery from Pauli noise via classical shadow
Zhu, Yan	Quantum Similarity Testing with Convolutional Neural Networks
Zoufal, Christa	On the Absence of Barren Plateaus in Quantum Generative Adversarial Networks

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