Guillaume Rabusseau

103 papers A* 11A 10B 1C 1Journal 68Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Grokking Finite-Dimensional Algebra. CoRR Pascal Tikeng Notsawo Jr., Guillaume Dumas, Guillaume Rabusseau
2026	—	`conf`	T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs. KDD (1) Alireza Dizaji, Benedict Aaron Tjandra, Mehrab Hamidi, Shenyang Huang, Guillaume Rabusseau
2025	J	`jnl`	Are Large Language Models Good Temporal Graph Learners? CoRR Shenyang Huang, Ali Parviz, Emma Kondrup, Zachary Yang, Zifeng Ding, Michael M. Bronstein, Reihaneh Rabbany, Guillaume Rabusseau
2025	J	`jnl`	Benefits and Limitations of Communication in Multi-Agent Reasoning. CoRR Michael Rizvi-Martel, Satwik Bhattamishra, Neil Rathi, Guillaume Rabusseau, Michael Hahn
2025	J	`jnl`	ClustRecNet: A Novel End-to-End Deep Learning Framework for Clustering Algorithm Recommendation. CoRR Mohammadreza Bakhtyari, Bogdan Mazoure, Renato Cordeiro de Amorim, Guillaume Rabusseau, Vladimir Makarenkov
2025	J	`jnl`	Efficient Probabilistic Tensor Networks. CoRR Marawan Gamal Abdel Hameed, Guillaume Rabusseau
2025	J	`jnl`	FlowQ-Net: A Generative Framework for Automated Quantum Circuit Design. CoRR Jun Dai, Michael Rizvi-Martel, Guillaume Rabusseau
2025	A*	`conf`	Grokking Beyond the Euclidean Norm of Model Parameters. ICML Pascal Tikeng Notsawo Jr., Guillaume Dumas, Guillaume Rabusseau
2025	J	`jnl`	Grokking Beyond the Euclidean Norm of Model Parameters. CoRR Pascal Tikeng Notsawo Jr., Guillaume Dumas, Guillaume Rabusseau
2025	J	`jnl`	Higher Order Transformers With Kronecker-Structured Attention. Trans. Mach. Learn. Res. Soroush Omranpour, Guillaume Rabusseau, Reihaneh Rabbany
2025	J	`jnl`	KQ-SVD: Compressing the KV Cache with Provable Guarantees on Attention Fidelity. CoRR Damien Lesens, Beheshteh T. Rakhshan, Guillaume Rabusseau
2025	J	`jnl`	Numerical PDE solvers outperform neural PDE solvers. CoRR Patrick Chatain, Michael Rizvi-Martel, Guillaume Rabusseau, Adam Oberman
2025	J	`jnl`	RL Fine-Tuning Heals OOD Forgetting in SFT. CoRR Hangzhan Jin, Sitao Luan, Sicheng Lyu, Guillaume Rabusseau, Reihaneh Rabbany, Doina Precup, Mohammad Hamdaqa
2025	J	`jnl`	T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs. CoRR Alireza Dizaji, Benedict Aaron Tjandra, Mehrab Hamidi, Shenyang Huang, Guillaume Rabusseau
2025	J	`jnl`	TGM: a Modular and Efficient Library for Machine Learning on Temporal Graphs. CoRR Jacob Chmura, Shenyang Huang, Tran Gia Bao Ngo, Ali Parviz, Farimah Poursafaei, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Matthias Fey, Reihaneh Rabbany
2025	J	`jnl`	Tractable Shapley Values and Interactions via Tensor Networks. CoRR Farzaneh Heidari, Chao Li, Guillaume Rabusseau
2024	A*	`conf`	A Tensor Decomposition Perspective on Second-order RNNs. ICML Maude Lizaire, Michael Rizvi-Martel, Marawan Gamal Abdel Hameed, Guillaume Rabusseau
2024	J	`jnl`	A Tensor Decomposition Perspective on Second-order RNNs. CoRR Maude Lizaire, Michael Rizvi-Martel, Marawan Gamal Abdel Hameed, Guillaume Rabusseau
2024	J	`jnl`	Connecting weighted automata, tensor networks and recurrent neural networks through spectral learning. Mach. Learn. Tianyu Li, Doina Precup, Guillaume Rabusseau
2024	A*	`conf`	Efficient Leverage Score Sampling for Tensor Train Decomposition. NeurIPS Vivek Bharadwaj, Beheshteh T. Rakhshan, Osman Asif Malik, Guillaume Rabusseau
2024	J	`jnl`	Efficient Leverage Score Sampling for Tensor Train Decomposition. CoRR Vivek Bharadwaj, Beheshteh T. Rakhshan, Osman Asif Malik, Guillaume Rabusseau
2024	J	`jnl`	GFlowNets for Hamiltonian decomposition in groups of compatible operators. CoRR Isaac L. Huidobro-Meezs, Jun Dai, Guillaume Rabusseau, Rodrigo A. Vargas-Hernández
2024	J	`jnl`	Higher Order Transformers: Efficient Attention Mechanism for Tensor Structured Data. CoRR Soroush Omranpour, Guillaume Rabusseau, Reihaneh Rabbany
2024	J	`jnl`	Higher Order Transformers: Enhancing Stock Movement Prediction On Multimodal Time-Series Data. CoRR Soroush Omranpour, Guillaume Rabusseau, Reihaneh Rabbany
2024	J	`jnl`	Laplacian Change Point Detection for Single and Multi-view Dynamic Graphs. ACM Trans. Knowl. Discov. Data Shenyang Huang, Samy Coulombe, Yasmeen Hitti, Reihaneh Rabbany, Guillaume Rabusseau
2024	A	`conf`	Length independent PAC-Bayes bounds for Simple RNNs. AISTATS Volodimir Mitarchuk, Clara Lacroce, Rémi Eyraud, Rémi Emonet, Amaury Habrard, Guillaume Rabusseau
2024	J	`jnl`	Optimal approximate minimization of one-letter weighted finite automata. Math. Struct. Comput. Sci. Clara Lacroce, Borja Balle, Prakash Panangaden, Guillaume Rabusseau
2024	J	`jnl`	ROSA: Random Subspace Adaptation for Efficient Fine-Tuning. CoRR Marawan Gamal Abdel Hameed, Aristides Milios, Siva Reddy, Guillaume Rabusseau
2024	J	`jnl`	Simulating Weighted Automata over Sequences and Trees with Transformers. CoRR Michael Rizvi, Maude Lizaire, Clara Lacroce, Guillaume Rabusseau
2024	A	`conf`	Simulating weighted automata over sequences and trees with transformers. AISTATS Michael Rizvi-Martel, Maude Lizaire, Clara Lacroce, Guillaume Rabusseau
2024	A*	`conf`	TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs. NeurIPS Julia Gastinger, Shenyang Huang, Michael Galkin, Erfan Loghmani, Ali Parviz, Farimah Poursafaei, Jacob Danovitch, Emanuele Rossi, Ioannis Koutis, Heiner Stuckenschmidt, Reihaneh Rabbany, Guillaume Rabusseau
2024	J	`jnl`	TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs. CoRR Julia Gastinger, Shenyang Huang, Mikhail Galkin, Erfan Loghmani, Ali Parviz, Farimah Poursafaei, Jacob Danovitch, Emanuele Rossi, Ioannis Koutis, Heiner Stuckenschmidt, Reihaneh Rabbany, Guillaume Rabusseau
2024	A*	`conf`	Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. ICLR Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters
2024	J	`jnl`	Towards Neural Scaling Laws for Foundation Models on Temporal Graphs. CoRR Razieh Shirzadkhani, Tran Gia Bao Ngo, Kiarash Shamsi, Shenyang Huang, Farimah Poursafaei, Poupak Azad, Reihaneh Rabbany, Baris Coskunuzer, Guillaume Rabusseau, Cuneyt Gurcan Akcora
2024	—	`conf`	UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs. LoG Shenyang Huang, Farimah Poursafaei, Reihaneh Rabbany, Guillaume Rabusseau, Emanuele Rossi
2024	J	`jnl`	UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs. CoRR Shenyang Huang, Farimah Poursafaei, Reihaneh Rabbany, Guillaume Rabusseau, Emanuele Rossi
2023	—	`conf`	Explaining Graph Neural Networks Using Interpretable Local Surrogates. TAG-ML Farzaneh Heidari, Perouz Taslakian, Guillaume Rabusseau
2023	—	`conf`	Fast and Attributed Change Detection on Dynamic Graphs with Density of States. PAKDD (1) Shenyang Huang, Jacob Danovitch, Guillaume Rabusseau, Reihaneh Rabbany
2023	J	`jnl`	Fast and Attributed Change Detection on Dynamic Graphs with Density of States. CoRR Shenyang Huang, Jacob Danovitch, Guillaume Rabusseau, Reihaneh Rabbany
2023	J	`jnl`	Generative Learning of Continuous Data by Tensor Networks. CoRR Alex Meiburg, Jing Chen, Jacob Miller, Raphaëlle Tihon, Guillaume Rabusseau, Alejandro Perdomo-Ortiz
2023	—	`ed.`	International Conference on Grammatical Inference, ICGI 2023, 10-13 July 2023, Rabat, Morocco. ICGI François Coste, Faissal Ouardi, Guillaume Rabusseau
2023	J	`jnl`	Laplacian Change Point Detection for Single and Multi-view Dynamic Graphs. CoRR Shenyang Huang, Samy Coulombe, Yasmeen Hitti, Reihaneh Rabbany, Guillaume Rabusseau
2023	J	`jnl`	Optimal Approximate Minimization of One-Letter Weighted Finite Automata. CoRR Clara Lacroce, Borja Balle, Prakash Panangaden, Guillaume Rabusseau
2023	A*	`conf`	Temporal Graph Benchmark for Machine Learning on Temporal Graphs. NeurIPS Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany
2023	J	`jnl`	Temporal Graph Benchmark for Machine Learning on Temporal Graphs. CoRR Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany
2023	J	`jnl`	Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. CoRR Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Ioannis Koutis, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters
2022	J	`jnl`	Approximate minimization of weighted tree automata. Inf. Comput. Borja Balle, Guillaume Rabusseau
2022	A*	`conf`	High-Order Pooling for Graph Neural Networks with Tensor Decomposition. NeurIPS Chenqing Hua, Guillaume Rabusseau, Jian Tang
2022	J	`jnl`	High-Order Pooling for Graph Neural Networks with Tensor Decomposition. CoRR Chenqing Hua, Guillaume Rabusseau, Jian Tang
2022	J	`jnl`	Low-Rank Representation of Reinforcement Learning Policies. J. Artif. Intell. Res. Bogdan Mazoure, Thang Doan, Tianyu Li, Vladimir Makarenkov, Joelle Pineau, Doina Precup, Guillaume Rabusseau
2022	J	`jnl`	Sequential Density Estimation via NCWFAs Sequential Density Estimation via Nonlinear Continuous Weighted Finite Automata. CoRR Tianyu Li, Bogdan Mazoure, Guillaume Rabusseau
2022	J	`jnl`	Spectral Regularization: an Inductive Bias for Sequence Modeling. CoRR Kaiwen Hou, Guillaume Rabusseau
2022	J	`jnl`	Towards an AAK Theory Approach to Approximate Minimization in the Multi-Letter Case. CoRR Clara Lacroce, Prakash Panangaden, Guillaume Rabusseau
2021	A	`conf`	A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix. AISTATS Thang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau, Pierre Alquier
2021	J	`jnl`	Estimating the Impact of an Improvement to a Revenue Management System: An Airline Application. CoRR Greta Laage, Emma Frejinger, William L. Hamilton, Andrea Lodi, Guillaume Rabusseau
2021	—	`conf`	Extracting Weighted Automata for Approximate Minimization in Language Modelling. ICGI Clara Lacroce, Prakash Panangaden, Guillaume Rabusseau
2021	J	`jnl`	Extracting Weighted Automata for Approximate Minimization in Language Modelling. CoRR Clara Lacroce, Prakash Panangaden, Guillaume Rabusseau
2021	A*	`conf`	Lower and Upper Bounds on the Pseudo-Dimension of Tensor Network Models. NeurIPS Behnoush Khavari, Guillaume Rabusseau
2021	J	`jnl`	Lower and Upper Bounds on the VC-Dimension of Tensor Network Models. CoRR Behnoush Khavari, Guillaume Rabusseau
2021	A*	`conf`	Optimal Spectral-Norm Approximate Minimization of Weighted Finite Automata. ICALP Borja Balle, Clara Lacroce, Prakash Panangaden, Doina Precup, Guillaume Rabusseau
2021	J	`jnl`	Optimal Spectral-Norm Approximate Minimization of Weighted Finite Automata. CoRR Borja Balle, Clara Lacroce, Prakash Panangaden, Doina Precup, Guillaume Rabusseau
2021	A	`conf`	Quantum Tensor Networks, Stochastic Processes, and Weighted Automata. AISTATS Sandesh Adhikary, Siddarth Srinivasan, Jacob Miller, Guillaume Rabusseau, Byron Boots
2021	J	`jnl`	Rademacher Random Projections with Tensor Networks. CoRR Beheshteh T. Rakhshan, Guillaume Rabusseau
2021	A	`conf`	Tensor Networks for Probabilistic Sequence Modeling. AISTATS Jacob Miller, Guillaume Rabusseau, John Terilla
2021	—	`conf`	Understanding Capacity Saturation in Incremental Learning. Canadian AI Shenyang Huang, Vincent François-Lavet, Guillaume Rabusseau
2020	J	`jnl`	A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix. CoRR Thang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau, Pierre Alquier
2020	J	`jnl`	Adaptive Tensor Learning with Tensor Networks. CoRR Meraj Hashemizadeh, Michelle Liu, Jacob Miller, Guillaume Rabusseau
2020	J	`jnl`	Connecting Weighted Automata, Tensor Networks and Recurrent Neural Networks through Spectral Learning. CoRR Tianyu Li, Doina Precup, Guillaume Rabusseau
2020	A	`conf`	Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning. AISTATS Tianyu Li, Bogdan Mazoure, Doina Precup, Guillaume Rabusseau
2020	A*	`conf`	Laplacian Change Point Detection for Dynamic Graphs. KDD Shenyang Huang, Yasmeen Hitti, Guillaume Rabusseau, Reihaneh Rabbany
2020	J	`jnl`	Laplacian Change Point Detection for Dynamic Graphs. CoRR Shenyang Huang, Yasmeen Hitti, Guillaume Rabusseau, Reihaneh Rabbany
2020	A*	`conf`	On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability (Extended Abstract). IJCAI Vincent François-Lavet, Guillaume Rabusseau, Joelle Pineau, Damien Ernst, Raphael Fonteneau
2020	J	`jnl`	Provably efficient reconstruction of policy networks. CoRR Bogdan Mazoure, Thang Doan, Tianyu Li, Vladimir Makarenkov, Joelle Pineau, Doina Precup, Guillaume Rabusseau
2020	J	`jnl`	Quantum Tensor Networks, Stochastic Processes, and Weighted Automata. CoRR Siddarth Srinivasan, Sandesh Adhikary, Jacob Miller, Guillaume Rabusseau, Byron Boots
2020	J	`jnl`	RandomNet: Towards Fully Automatic Neural Architecture Design for Multimodal Learning. CoRR Stefano Alletto, Shenyang Huang, Vincent François-Lavet, Yohei Nakata, Guillaume Rabusseau
2020	J	`jnl`	Tensor Networks for Language Modeling. CoRR Jacob Miller, Guillaume Rabusseau, John Terilla
2020	A	`conf`	Tensorized Random Projections. AISTATS Beheshteh T. Rakhshan, Guillaume Rabusseau
2020	J	`jnl`	Tensorized Random Projections. CoRR Beheshteh T. Rakhshan, Guillaume Rabusseau
2019	A	`conf`	Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning. AISTATS Guillaume Rabusseau, Tianyu Li, Doina Precup
2019	J	`jnl`	Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning. CoRR Tianyu Li, Bogdan Mazoure, Doina Precup, Guillaume Rabusseau
2019	J	`jnl`	Neural Architecture Search for Class-incremental Learning. CoRR Shenyang Huang, Vincent François-Lavet, Guillaume Rabusseau
2019	J	`jnl`	On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability. J. Artif. Intell. Res. Vincent François-Lavet, Guillaume Rabusseau, Joelle Pineau, Damien Ernst, Raphael Fonteneau
2019	J	`jnl`	Recognizable series on graphs and hypergraphs. J. Comput. Syst. Sci. Raphaël Bailly, Guillaume Rabusseau, François Denis
2018	J	`jnl`	Clustering-Oriented Representation Learning with Attractive-Repulsive Loss. CoRR Kian Kenyon-Dean, Andre Cianflone, Lucas Page-Caccia, Guillaume Rabusseau, Jackie Chi Kit Cheung, Doina Precup
2018	J	`jnl`	Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning. CoRR Guillaume Rabusseau, Tianyu Li, Doina Precup
2018	J	`jnl`	Hierarchical Methods of Moments. CoRR Matteo Ruffini, Guillaume Rabusseau, Borja Balle
2018	—	`conf`	Learning Graph Weighted Models on Pictures. ICGI Philip Amortila, Guillaume Rabusseau
2018	J	`jnl`	Learning Graph Weighted Models on Pictures. CoRR Philip Amortila, Guillaume Rabusseau
2018	B	`conf`	Minimization of Graph Weighted Models over Circular Strings. FoSSaCS Guillaume Rabusseau
2018	A	`conf`	Nonlinear Weighted Finite Automata. AISTATS Tianyu Li, Guillaume Rabusseau, Doina Precup
2018	J	`jnl`	Sequential Coordination of Deep Models for Learning Visual Arithmetic. CoRR Eric Crawford, Guillaume Rabusseau, Joelle Pineau
2017	—	`conf`	Hierarchical Methods of Moments. NIPS Matteo Ruffini, Guillaume Rabusseau, Borja Balle
2017	—	`conf`	Multitask Spectral Learning of Weighted Automata. NIPS Guillaume Rabusseau, Borja Balle, Joelle Pineau
2017	J	`jnl`	Neural Network Based Nonlinear Weighted Finite Automata. CoRR Tianyu Li, Guillaume Rabusseau, Doina Precup
2017	J	`jnl`	Tensor Regression Networks with various Low-Rank Tensor Approximations. CoRR Xingwei Cao, Guillaume Rabusseau, Joelle Pineau
2016	J	`jnl`	Higher-Order Low-Rank Regression. CoRR Guillaume Rabusseau, Hachem Kadri
2016	A	`conf`	Low-Rank Approximation of Weighted Tree Automata. AISTATS Guillaume Rabusseau, Borja Balle, Shay B. Cohen
2016	—	`conf`	Low-Rank Regression with Tensor Responses. NIPS Guillaume Rabusseau, Hachem Kadri
2015	C	`conf`	Recognizable Series on Hypergraphs. LATA Raphaël Bailly, François Denis, Guillaume Rabusseau
2015	J	`jnl`	Weighted Tree Automata Approximation by Singular Value Truncation. CoRR Guillaume Rabusseau, Borja Balle, Shay B. Cohen
2014	J	`jnl`	Learning Negative Mixture Models by Tensor Decompositions. CoRR Guillaume Rabusseau, François Denis
2014	—	`conf`	Maximizing a Tree Series in the Representation Space. ICGI Guillaume Rabusseau, François Denis
2014	J	`jnl`	Recognizable Series on Hypergraphs. CoRR Raphaël Bailly, François Denis, Guillaume Rabusseau