Roberto Bondesan

According to our database, Roberto Bondesan authored at least 16 papers between 2019 and 2023.

Collaborative distances:

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

2023

Efficient Learning of Long-Range and Equivariant Quantum Systems.

Stepán Smíd, Roberto Bondesan

CoRR, 2023

The END: An Equivariant Neural Decoder for Quantum Error Correction.

Evgenii Egorov, Roberto Bondesan, Max Welling

CoRR, 2023

Robust Scheduling with GFlowNets.

David W. Zhang, Corrado Rainone, Markus Peschl, Roberto Bondesan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Neural Simulated Annealing.

Alvaro H. C. Correia, Daniel E. Worrall, Roberto Bondesan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

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

Learning Lattice Quantum Field Theories with Equivariant Continuous Flows.

Mathis Gerdes, Pim de Haan, Corrado Rainone, Roberto Bondesan, Miranda C. N. Cheng

CoRR, 2022

Batch Bayesian Optimization on Permutations using the Acquisition Weighted Kernel.

ChangYong Oh, Roberto Bondesan, Efstratios Gavves, Max Welling

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Perturbations for Soft-Output Linear MIMO Demappers.

Daniel E. Worrall, Markus Peschl, Arash Behboodi, Roberto Bondesan

Proceedings of the IEEE Global Communications Conference, 2022

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

Deterministic Gibbs Sampling via Ordinary Differential Equations.

Kirill Neklyudov, Roberto Bondesan, Max Welling

CoRR, 2021

Batch Bayesian Optimization on Permutations using Acquisition Weighted Kernels.

ChangYong Oh, Roberto Bondesan, Efstratios Gavves, Max Welling

CoRR, 2021

The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning.

Roberto Bondesan, Max Welling

Proceedings of the 38th International Conference on Machine Learning, 2021

Probabilistic Numeric Convolutional Neural Networks.

Marc Anton Finzi, Roberto Bondesan, Max Welling

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Quantum Deformed Neural Networks.

Roberto Bondesan, Max Welling

CoRR, 2020

2019

Learning Symmetries of Classical Integrable Systems.

Roberto Bondesan, Austen Lamacraft

CoRR, 2019