E-LIB Suche - Ergebnisse für: Rabusseau, Guillaume

1

Laplacian Change Point Detection for Single and Multi-view ..:

Huang, Shenyang ; Coulombe, Samy ; Hitti, Yasmeen..
ACM Transactions on Knowledge Discovery from Data. 18 (2024) 3 - p. 1-32 , 2024

Link: https://doi.org/10.1145/..

2

Fast and Attributed Change Detection on Dynamic Graphs with..:

, In: Advances in Knowledge Discovery and Data Mining; Lecture Notes in Computer Science,

Huang, Shenyang ; Danovitch, Jacob ; Rabusseau, Guillaume. - p. 15-26 , 2023

Link: https://doi.org/10.1007/..

3

Approximate minimization of weighted tree automata:

Balle, Borja ; Rabusseau, Guillaume
Information and Computation. 282 (2022) - p. 104654 , 2022

Link: https://doi.org/10.1016/..

4

Connecting weighted automata, tensor networks and recurrent..:

Li, Tianyu ; Precup, Doina ; Rabusseau, Guillaume
Machine Learning. 113 (2022) 5 - p. 2619-2653 , 2022

Link: https://doi.org/10.1007/..

5

Horizontal gene transfer and recombination analysis of SARS..:

Makarenkov, Vladimir ; Mazoure, Bogdan ; Rabusseau, Guillaume.
BMC Ecology and Evolution. 21 (2021) 1 - p. , 2021

Link: https://doi.org/10.1186/..

6

Laplacian Change Point Detection for Dynamic Graphs:

, In: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining,

Huang, Shenyang ; Hitti, Yasmeen ; Rabusseau, Guillaume. - p. 349-358 , 2020

Link: https://dl.acm.org/doi/1..

7

Recognizable series on graphs and hypergraphs:

Bailly, Raphaël ; Rabusseau, Guillaume ; Denis, François
Journal of Computer and System Sciences. 104 (2019) - p. 58-81 , 2019

Link: https://doi.org/10.1016/..

8

Minimization of Graph Weighted Models over Circular Strings:

, In: Lecture Notes in Computer Science; Foundations of Software Science and Computation Structures,

Rabusseau, Guillaume - p. 513-529 , 2018

Link: https://doi.org/10.1007/..

9

Length Independent PAC-Bayes Bounds for Simple RNNs:

Mitarchuk, Volodimir ; Lacroce, Clara ; Eyraud, Rémi...
hal-04488664. , 2024

Link: https://hal.science/hal-..

10

Towards Foundational Models for Molecular Learning on Large..:

Beaini, Dominique ; Huang, Shenyang ; Cunha, Joao Alex...
doi:10.5281/zenodo.8370547. , 2023

Link: https://zenodo.org/recor..

11

Towards Foundational Models for Molecular Learning on Large..:

Beaini, Dominique ; Huang, Shenyang ; Cunha, Joao Alex...
doi:10.5281/zenodo.7998401. , 2023

Link: https://zenodo.org/recor..

12

Temporal Graph Benchmark for Machine Learning on Temporal G..:

Huang, Shenyang ; Poursafaei, Farimah ; Danovitch, Jacob...
http://arxiv.org/abs/2307.01026. , 2023

Link: http://arxiv.org/abs/230..

13

Optimal Approximate Minimization of One-Letter Weighted Fin..:

Lacroce, Clara ; Balle, Borja ; Panangaden, Prakash.
http://arxiv.org/abs/2306.00135. , 2023

Link: http://arxiv.org/abs/230..

14

Towards Foundational Models for Molecular Learning on Large..:

Beaini, Dominique ; Huang, Shenyang ; Cunha, Joao Alex...
http://arxiv.org/abs/2310.04292. , 2023

Link: http://arxiv.org/abs/231..

15

Generative Learning of Continuous Data by Tensor Networks:

Meiburg, Alex ; Chen, Jing ; Miller, Jacob...
http://arxiv.org/abs/2310.20498. , 2023

Link: http://arxiv.org/abs/231..