Publications and preprints
My publications and preprints can be found on my Google Scholar page, or on arXiv.
2025
B. Even, L. Ganassali. Statistical–computational gap in multiple Gaussian graph alignment, to appear. [arXiv]
L. De Lara, L. Ganassali. What is a good matching of probability measures? A counterfactual lens on transport maps, submitted. [arXiv]
2024
M. Even, L. Ganassali, J. Maier, L. Massoulié. Aligning Embeddings and Geometric Random Graphs: Informational Results and Computational Approaches for the Procrustes-Wasserstein Problem, NeurIPS 2024. [NeurIPS presentation] [arXiv]
2023
F. Jamshidi, L. Ganassali, N. Kiyavash. On sample complexity of conditional independence testing with Von Mises estimator with application to causal discovery, ICML 2024. [PMLR] [arXiv]
S. Akbari, L. Ganassali, N. Kiyavash. Learning causal graphs via monotone triangular transport maps, NeurIPS 2023 Workshop on Optimal Transport and Machine Learning. [arXiv]
2022
L. Ganassali, L. Massoulié, G. Semerjian. Statistical limits of correlation detection in trees, Annals of Applied Probability. [journal] [arXiv]
L. Ganassali. The graph alignment problem: fundamental limits and efficient algorithms, PhD dissertation. [pdf] [arXiv]
2021
L. Ganassali, M. Lelarge, L. Massoulié. Correlation detection in trees for partial graph alignment, Annals of Applied Probability (short version published at ITCS 2022). [journal] [ITCS] [arXiv]
L. Ganassali, M. Lelarge, L. Massoulié. Impossibility of Partial Recovery in the Graph Alignment Problem, COLT 2021. [PMLR] [COLT presentation] [arXiv]
2020
L. Ganassali. Sharp threshold for alignment of graph databases with Gaussian weights, MSML 2021. [PMLR] [MSML presentation] [arXiv]
M. Akian, L. Ganassali, S. Gaubert, L. Massoulié. Probabilistic and mean-field model of COVID-19 epidemics with user mobility and contact tracing, 2020, preprint. [arXiv]
L. Ganassali, L. Massoulié. From tree matching to sparse graph alignment, COLT 2020. [PMLR] [COLT presentation] [arXiv]