Michael Spannowsky

According to our database, Michael Spannowsky authored at least 26 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Improved Ground State Estimation in Quantum Field Theories via Normalising Flow-Assisted Neural Quantum States.

Vishal S. Ngairangbam, Michael Spannowsky, Timur Sypchenko

CoRR, June, 2025

Enhancing anomaly detection with topology-aware autoencoders.

Vishal S. Ngairangbam, Blazej Rozwoda, Kazuki Sakurai, Michael Spannowsky

CoRR, February, 2025

Communicating Likelihoods with Normalising Flows.

Jack Y. Araz, Anja Beck, Méril Reboud, Michael Spannowsky, Danny van Dyk

CoRR, February, 2025

Generating quantum reservoir state representations with random matrices.

Samuel Tovey, Tobias Fellner, Christian Holm, Michael Spannowsky

Mach. Learn. Sci. Technol., 2025

Optimal equivariant architectures from the symmetries of matrix-element likelihoods.

Daniel Maître, Vishal S. Ngairangbam, Michael Spannowsky

Mach. Learn. Sci. Technol., 2025

2024

Quantum pathways for charged track finding in high-energy collisions.

Christopher Brown, Michael Spannowsky, Alexander Tapper, Simon Williams, Ioannis Xiotidis

Frontiers Artif. Intell., 2024

Training neural networks with universal adiabatic quantum computing.

Steve Abel, Juan Carlos Criado, Michael Spannowsky

Frontiers Artif. Intell., 2024

FeynMG: A FeynRules extension for scalar-tensor theories of gravity.

Sergio Sevillano Muñoz, Edmund J. Copeland, Peter Millington, Michael Spannowsky

Comput. Phys. Commun., 2024

Collective variables of neural networks: empirical time evolution and scaling laws.

Samuel Tovey, Sven Krippendorf, Michael Spannowsky, Konstantin Nikolaou, Christian Holm

CoRR, 2024

The role of data embedding in quantum autoencoders for improved anomaly detection.

Jack Y. Araz, Michael Spannowsky

CoRR, 2024

Optimal Symmetries in Binary Classification.

Vishal S. Ngairangbam, Michael Spannowsky

CoRR, 2024

Generating Reservoir State Descriptions with Random Matrices.

Samuel Tovey, Christian Holm, Michael Spannowsky

CoRR, 2024

2023

Generative Invertible Quantum Neural Networks.

Armand Rousselot, Michael Spannowsky

CoRR, 2023

2022

A duality connecting neural network and cosmological dynamics.

Sven Krippendorf, Michael Spannowsky

Mach. Learn. Sci. Technol., 2022

IRC-Safe Graph Autoencoder for Unsupervised Anomaly Detection.

Oliver Atkinson, Akanksha Bhardwaj, Christoph Englert, Partha Konar, Vishal S. Ngairangbam, Michael Spannowsky

Frontiers Artif. Intell., 2022

Unsupervised Quark/Gluon Jet Tagging With Poissonian Mixture Models.

Ezequiel Alvarez, Michael Spannowsky, Manuel Szewc

Frontiers Artif. Intell., 2022

Quantum-probabilistic Hamiltonian learning for generative modelling & anomaly detection.

Jack Y. Araz, Michael Spannowsky

CoRR, 2022

A Genetic Quantum Annealing Algorithm.

Steven Abel, Luca A. Nutricati, Michael Spannowsky

CoRR, 2022

Identifying (anti-)skyrmions while they form.

Jack Y. Araz, Juan Carlos Criado, Michael Spannowsky

CoRR, 2022

IRC-safe Graph Autoencoder for an unsupervised anomaly detection.

Oliver Atkinson, Akanksha Bhardwaj, Christoph Englert, Partha Konar, Vishal S. Ngairangbam, Michael Spannowsky

CoRR, 2022

Qade: Solving Differential Equations on Quantum Annealers.

Juan Carlos Criado, Michael Spannowsky

CoRR, 2022

Completely Quantum Neural Networks.

Steve Abel, Juan Carlos Criado, Michael Spannowsky

CoRR, 2022

Classical versus Quantum: comparing Tensor Network-based Quantum Circuits on LHC data.

Jack Y. Araz, Michael Spannowsky

CoRR, 2022

2021

Quantum-inspired event reconstruction with Tensor Networks: Matrix Product States.

Jack Y. Araz, Michael Spannowsky

CoRR, 2021

Quantum Optimisation of Complex Systems with a Quantum Annealer.

Steve Abel, Andrew Blance, Michael Spannowsky

CoRR, 2021

Elvet - a neural network-based differential equation and variational problem solver.

Jack Y. Araz, Juan Carlos Criado, Michael Spannowsky

CoRR, 2021