Learning Symmetries of Classical Integrable Systems. - Roberto Bondesan; Austen Lamacraft (CoRR, 2019)

Quantum Deformed Neural Networks. - Roberto Bondesan; Max Welling (CoRR, 2020)

Probabilistic Numeric Convolutional Neural Networks. - Marc Anton Finzi; Roberto Bondesan; Max Welling (ICLR, 2021)

The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning. - Roberto Bondesan; Max Welling (ICML, 2021)

Batch Bayesian Optimization on Permutations using Acquisition Weighted Kernels. - ChangYong Oh; Roberto Bondesan; Efstratios Gavves; Max Welling (CoRR, 2021)

Deterministic Gibbs Sampling via Ordinary Differential Equations. - Kirill Neklyudov; Roberto Bondesan; Max Welling (CoRR, 2021)

Scaling Up Machine Learning For Quantum Field Theory with Equivariant Continuous Flows. - Pim de Haan; Corrado Rainone; Miranda C. N. Cheng; Roberto Bondesan (CoRR, 2021)

Learning Perturbations for Soft-Output Linear MIMO Demappers. - Daniel E. Worrall; Markus Peschl; Arash Behboodi; Roberto Bondesan (GLOBECOM, 2022)

Neural Topological Ordering for Computation Graphs. - Mukul Gagrani; Corrado Rainone; Yang Yang; Harris Teague; Wonseok Jeon; Roberto Bondesan; Herke van Hoof; Christopher Lott; Weiliang Will Zeng; Piero Zappi (NeurIPS, 2022)

Batch Bayesian Optimization on Permutations using the Acquisition Weighted Kernel. - ChangYong Oh; Roberto Bondesan; Efstratios Gavves; Max Welling (NeurIPS, 2022)

Learning Lattice Quantum Field Theories with Equivariant Continuous Flows. - Mathis Gerdes; Pim de Haan; Corrado Rainone; Roberto Bondesan; Miranda C. N. Cheng (CoRR, 2022)

Bayesian Optimization for Macro Placement. - ChangYong Oh; Roberto Bondesan; Dana Kianfar; Rehan Ahmed; Rishubh Khurana; Payal Agarwal; Romain Lepert; Mysore Sriram; Max Welling (CoRR, 2022)

Neural Simulated Annealing. - Alvaro H. C. Correia; Daniel E. Worrall; Roberto Bondesan (AISTATS, 2023)

Robust Scheduling with GFlowNets. - David W. Zhang; Corrado Rainone; Markus Peschl; Roberto Bondesan (ICLR, 2023)

The END: An Equivariant Neural Decoder for Quantum Error Correction. - Evgenii Egorov; Roberto Bondesan; Max Welling (CoRR, 2023)

Accurate Learning of Equivariant Quantum Systems from a Single Ground State. - Stepán Smíd; Roberto Bondesan (CoRR, 2024)

Continuous normalizing flows for lattice gauge theories. - Mathis Gerdes; Pim de Haan; Roberto Bondesan; Miranda C. N. Cheng (CoRR, 2024)

Efficient Learning of Long-Range and Equivariant Quantum Systems. - Stepán Smíd; Roberto Bondesan (Quantum, 2025)

Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts. - Marta Skreta; Tara Akhound-Sadegh; Viktor Ohanesian; Roberto Bondesan; Alán Aspuru-Guzik; Arnaud Doucet; Rob Brekelmans; Alexander Tong 001; Kirill Neklyudov (CoRR, 2025)

Assessing Quantum Advantage for Gaussian Process Regression. - Dominic Lowe; M. S. Kim; Roberto Bondesan (CoRR, 2025)