Michael Spannowsky

36 papers Journal 36
YearRankTypeTitle / Venue / Authors
2026 J jnl
From Reachability to Learnability: Geometric Design Principles for Quantum Neural Networks.
CoRR
Vishal S. Ngairangbam, Michael Spannowsky
2026 J jnl
Theory-informed neural networks for particle physics.
Mach. Learn. Sci. Technol.
Barry M. Dillon, Michael Spannowsky
2025 J jnl
Another Fit Bites the Dust: Conformal Prediction as a Calibration Standard for Machine Learning in High-Energy Physics.
CoRR
Jack Y. Araz, Michael Spannowsky
2025 J jnl
Collective variables of neural networks: empirical time evolution and scaling laws.
Mach. Learn. Sci. Technol.
Samuel Tovey, Sven Krippendorf, Michael Spannowsky, Konstantin Nikolaou, Christian Holm
2025 J jnl
Communicating Likelihoods with Normalising Flows.
CoRR
Jack Y. Araz, Anja Beck, Méril Reboud, Michael Spannowsky, Danny van Dyk
2025 J jnl
Enhancing anomaly detection with topology-aware autoencoders.
CoRR
Vishal S. Ngairangbam, Blazej Rozwoda, Kazuki Sakurai, Michael Spannowsky
2025 J jnl
Enhancing anomaly detection with topology-aware autoencoders.
Mach. Learn. Sci. Technol.
Vishal S. Ngairangbam, Blazej Rozwoda, Kazuki Sakurai, Michael Spannowsky
2025 J jnl
Generating quantum reservoir state representations with random matrices.
Mach. Learn. Sci. Technol.
Samuel Tovey, Tobias Fellner, Christian Holm, Michael Spannowsky
2025 J jnl
Improved Ground State Estimation in Quantum Field Theories via Normalising Flow-Assisted Neural Quantum States.
CoRR
Vishal S. Ngairangbam, Michael Spannowsky, Timur Sypchenko
2025 J jnl
Optimal equivariant architectures from the symmetries of matrix-element likelihoods.
Mach. Learn. Sci. Technol.
Daniel Maître, Vishal S. Ngairangbam, Michael Spannowsky
2025 J jnl
QINNs: Quantum-Informed Neural Networks.
CoRR
Aritra Bal, Markus Klute, Benedikt Maier, Melik Oughton, Eric Pezone, Michael Spannowsky
2025 J jnl
Stable and Interpretable Jet Physics with IRC-Safe Equivariant Feature Extraction.
CoRR
Partha Konar, Vishal S. Ngairangbam, Michael Spannowsky, Deepanshu Srivastava
2024 J jnl
Collective variables of neural networks: empirical time evolution and scaling laws.
CoRR
Samuel Tovey, Sven Krippendorf, Michael Spannowsky, Konstantin Nikolaou, Christian Holm
2024 J jnl
FeynMG: A FeynRules extension for scalar-tensor theories of gravity.
Comput. Phys. Commun.
Sergio Sevillano Muñoz, Edmund J. Copeland, Peter Millington, Michael Spannowsky
2024 J jnl
Generating Reservoir State Descriptions with Random Matrices.
CoRR
Samuel Tovey, Christian Holm, Michael Spannowsky
2024 J jnl
Optimal Equivariant Architectures from the Symmetries of Matrix-Element Likelihoods.
CoRR
Daniel Maître, Vishal S. Ngairangbam, Michael Spannowsky
2024 J jnl
Optimal Symmetries in Binary Classification.
CoRR
Vishal S. Ngairangbam, Michael Spannowsky
2024 J jnl
Quantum pathways for charged track finding in high-energy collisions.
Frontiers Artif. Intell.
Christopher Brown, Michael Spannowsky, Alexander D. Tapper, Simon Williams, Ioannis Xiotidis
2024 J jnl
The role of data embedding in quantum autoencoders for improved anomaly detection.
CoRR
Jack Y. Araz, Michael Spannowsky
2024 J jnl
Training neural networks with universal adiabatic quantum computing.
Frontiers Artif. Intell.
Steve Abel, Juan Carlos Criado, Michael Spannowsky
2023 J jnl
Generative Invertible Quantum Neural Networks.
CoRR
Armand Rousselot, Michael Spannowsky
2023 J jnl
Training Neural Networks with Universal Adiabatic Quantum Computing.
CoRR
Steve Abel, Juan Carlos Criado, Michael Spannowsky
2022 J jnl
A Genetic Quantum Annealing Algorithm.
CoRR
Steven Abel, Luca A. Nutricati, Michael Spannowsky
2022 J jnl
A duality connecting neural network and cosmological dynamics.
CoRR
Sven Krippendorf, Michael Spannowsky
2022 J jnl
A duality connecting neural network and cosmological dynamics.
Mach. Learn. Sci. Technol.
Sven Krippendorf, Michael Spannowsky
2022 J jnl
Classical versus Quantum: comparing Tensor Network-based Quantum Circuits on LHC data.
CoRR
Jack Y. Araz, Michael Spannowsky
2022 J jnl
Completely Quantum Neural Networks.
CoRR
Steve Abel, Juan Carlos Criado, Michael Spannowsky
2022 J jnl
IRC-Safe Graph Autoencoder for Unsupervised Anomaly Detection.
Frontiers Artif. Intell.
Oliver Atkinson, Akanksha Bhardwaj, Christoph Englert, Partha Konar, Vishal S. Ngairangbam, Michael Spannowsky
2022 J jnl
IRC-safe Graph Autoencoder for an unsupervised anomaly detection.
CoRR
Oliver Atkinson, Akanksha Bhardwaj, Christoph Englert, Partha Konar, Vishal S. Ngairangbam, Michael Spannowsky
2022 J jnl
Identifying (anti-)skyrmions while they form.
CoRR
Jack Y. Araz, Juan Carlos Criado, Michael Spannowsky
2022 J jnl
Qade: Solving Differential Equations on Quantum Annealers.
CoRR
Juan Carlos Criado, Michael Spannowsky
2022 J jnl
Quantum-probabilistic Hamiltonian learning for generative modelling & anomaly detection.
CoRR
Jack Y. Araz, Michael Spannowsky
2022 J jnl
Unsupervised Quark/Gluon Jet Tagging With Poissonian Mixture Models.
Frontiers Artif. Intell.
Ezequiel Alvarez, Michael Spannowsky, Manuel Szewc
2021 J jnl
Elvet - a neural network-based differential equation and variational problem solver.
CoRR
Jack Y. Araz, Juan Carlos Criado, Michael Spannowsky
2021 J jnl
Quantum Optimisation of Complex Systems with a Quantum Annealer.
CoRR
Steve Abel, Andrew Blance, Michael Spannowsky
2021 J jnl
Quantum-inspired event reconstruction with Tensor Networks: Matrix Product States.
CoRR
Jack Y. Araz, Michael Spannowsky