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2020 – today
- 2024
[i16]Stepán Smíd, Roberto Bondesan:
Accurate Learning of Equivariant Quantum Systems from a Single Ground State. CoRR abs/2405.12309 (2024)- 2023
- [c7]Alvaro H. C. Correia, Daniel E. Worrall, Roberto Bondesan:
Neural Simulated Annealing. AISTATS 2023: 4946-4962 - [c6]David W. Zhang, Corrado Rainone, Markus Peschl, Roberto Bondesan:
Robust Scheduling with GFlowNets. ICLR 2023 - [i15]David W. Zhang, Corrado Rainone, Markus Peschl, Roberto Bondesan:
Robust Scheduling with GFlowNets. CoRR abs/2302.05446 (2023) - [i14]Evgenii Egorov, Roberto Bondesan, Max Welling:
The END: An Equivariant Neural Decoder for Quantum Error Correction. CoRR abs/2304.07362 (2023) - [i13]Stepán Smíd, Roberto Bondesan:
Efficient Learning of Long-Range and Equivariant Quantum Systems. CoRR abs/2312.17019 (2023) - 2022
- [c5]Daniel E. Worrall, Markus Peschl, Arash Behboodi, Roberto Bondesan:
Learning Perturbations for Soft-Output Linear MIMO Demappers. GLOBECOM 2022: 5213-5218 - [c4]Mukul Gagrani, Corrado Rainone, Yang Yang, Harris Teague, Wonseok Jeon, Roberto Bondesan, Herke van Hoof, Christopher Lott, Weiliang Will Zeng, Piero Zappi:
Neural Topological Ordering for Computation Graphs. NeurIPS 2022 - [c3]ChangYong Oh, Roberto Bondesan, Efstratios Gavves, Max Welling:
Batch Bayesian Optimization on Permutations using the Acquisition Weighted Kernel. NeurIPS 2022 - [i12]Alvaro H. C. Correia, Daniel E. Worrall, Roberto Bondesan:
Neural Simulated Annealing. CoRR abs/2203.02201 (2022) - [i11]Mathis Gerdes, Pim de Haan, Corrado Rainone, Roberto Bondesan, Miranda C. N. Cheng:
Learning Lattice Quantum Field Theories with Equivariant Continuous Flows. CoRR abs/2207.00283 (2022) - [i10]Mukul Gagrani, Corrado Rainone, Yang Yang, Harris Teague, Wonseok Jeon, Herke van Hoof, Weiliang Will Zeng, Piero Zappi, Christopher Lott, Roberto Bondesan:
Neural Topological Ordering for Computation Graphs. CoRR abs/2207.05899 (2022) - [i9]ChangYong Oh, Roberto Bondesan, Dana Kianfar, Rehan Ahmed, Rishubh Khurana, Payal Agarwal, Romain Lepert, Mysore Sriram, Max Welling:
Bayesian Optimization for Macro Placement. CoRR abs/2207.08398 (2022) - [i8]Daniel E. Worrall, Markus Peschl, Arash Behboodi, Roberto Bondesan:
Learning Perturbations for Soft-Output Linear MIMO Demappers. CoRR abs/2209.00529 (2022) - 2021
- [c2]Marc Anton Finzi, Roberto Bondesan, Max Welling:
Probabilistic Numeric Convolutional Neural Networks. ICLR 2021 - [c1]Roberto Bondesan, Max Welling:
The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning. ICML 2021: 1038-1048 - [i7]ChangYong Oh, Roberto Bondesan, Efstratios Gavves, Max Welling:
Batch Bayesian Optimization on Permutations using Acquisition Weighted Kernels. CoRR abs/2102.13382 (2021) - [i6]Roberto Bondesan, Max Welling:
The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning. CoRR abs/2103.04913 (2021) - [i5]Kirill Neklyudov, Roberto Bondesan, Max Welling:
Deterministic Gibbs Sampling via Ordinary Differential Equations. CoRR abs/2106.10188 (2021) - [i4]Pim de Haan, Corrado Rainone, Miranda C. N. Cheng, Roberto Bondesan:
Scaling Up Machine Learning For Quantum Field Theory with Equivariant Continuous Flows. CoRR abs/2110.02673 (2021) - 2020
- [i3]Marc Finzi, Roberto Bondesan, Max Welling:
Probabilistic Numeric Convolutional Neural Networks. CoRR abs/2010.10876 (2020) - [i2]Roberto Bondesan, Max Welling:
Quantum Deformed Neural Networks. CoRR abs/2010.11189 (2020)
2010 – 2019
- 2019
- [i1]Roberto Bondesan, Austen Lamacraft:
Learning Symmetries of Classical Integrable Systems. CoRR abs/1906.04645 (2019)
Coauthor Index
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