Publications

Scholar

Orcid

Journal articles

1. Thouvenin, P.-A., Repetti, A., & Chainais, P. (2023). A Distributed Split-Gibbs Sampler with Hypergraph Structure for High-Dimensional Inverse Problems. J. Comput. and Graph. Stat.
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2. Palud, P., Einig, L., Le Petit, F., Bron, É., Chainais, P., Chanussot, J., Pety, J., Thouvenin, P.-A., Languignon, D., Bešlić, I., Santa-Maria, M. G., Orkisz, J. H., Ségal, L. E., Zakardjian, A., Bardeau, S., Gerin, M., Goicoechea, J. R., Gratier, P., Guzman, V. V., … Sievers, A. (2023). Neural network-based emulation of interstellar medium models. A & A, 678, A198.
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3. Palud, P., Thouvenin, P.-A., Chainais, P., Bron, E., & Le Petit, F. (2023). Efficient sampling of non log-concave posterior distributions with mixture of noises. IEEE Trans. Signal Process., 71, 2491–2501.
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4. Thouvenin, P.-A., Abdulaziz, A., Dabbech, A., Repetti, A., & Wiaux, Y. (2023). Parallel faceted imaging in radio interferometry via proximal splitting (Faceted HyperSARA): I. Algorithm and simulations. Mon. Not. R. Astron. Soc., 521(1), 1–19.
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5. Thouvenin, P.-A., Dabbech, A., Jiang, M., Abdulaziz, A., Thiran, J.-P., Jackson, A., & Wiaux, Y. (2023). Parallel faceted imaging in radio interferometry via proximal splitting (Faceted HyperSARA): II. Code and real data proof of concept. Mon. Not. R. Astron. Soc., 521(1), 20–34.
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6. Thouvenin, P.-A., Dobigeon, N., & Tourneret, J.-Y. (2019). Partially asynchronous distributed unmixing of hyperspectral images. IEEE Trans. Geosci. Remote Sens., 57(4), 2009–2021.
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7. Thouvenin, P.-A., Dobigeon, N., & Tourneret, J.-Y. (2018). A hierarchical Bayesian model accounting for endmember variability and abrupt spectral changes to unmix multitemporal hyperspectral images. IEEE Trans. Comput. Imag., 4(1), 32–45.
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8. Thouvenin, P.-A., Dobigeon, N., & Tourneret, J.-Y. (2016). Online unmixing of multitemporal hyperspectral images accounting for spectral variability. IEEE Trans. Image Process., 25(9), 3979–3990.
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9. Thouvenin, P.-A., Dobigeon, N., & Tourneret, J.-Y. (2016). Hyperspectral Unmixing with Spectral Variability Using a Perturbed Linear Mixing Model. IEEE Trans. Signal Process., 64(2), 525–538.
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International conferences

1. Palud, P., Chainais, P., Le Petit, F., Bron, E., Thouvenin, P.-A., Vono, M., Einig, L., Santa-Maria, M. G., Gaudel, M., Orkisz, J. H., de Souza Magalhaes, V., Bardeau, S., Gerin, M., Goicoechea, J. R., Gratier, P., Guzman, V. V., Kainulainen, J., Levrier, F., Peretto, N., … Sievers, A. (2022). Mixture of noises and sampling of non-log-concave posterior distributions. Proc. European Signal Process. Conf. (EUSIPCO), 2031–2035.
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2. Thouvenin, P.-A., Repetti, A., & Chainais, P. (2022). A versatile distributed MCMC algorithm for large scale inverse problems. Proc. European Signal Process. Conf. (EUSIPCO), 2016–2020.
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3. Thouvenin, P.-A., Abdulaziz, A., Jiang, M., Repetti, A., Dabbech, A., & Wiaux, Y. (2020, December). A Faceted Prior fo Scalable Wideband Imaging: Application to Radio Astronomy. Proc. IEEE Int. Workshop Comput. Adv. Multi-Sensor Adaptive Process. (CAMSAP).
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4. Thouvenin, P.-A., Abdulaziz, A., Jiang, M., Repetti, A., & Wiaux, Y. (2019). A Faceted Prior for Scalable Wideband Computational Imaging. Spars, 1–5.
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5. Thouvenin, P.-A., Repetti, A., Dabbech, A., & Wiaux, Y. (2018). Time-Regularized Blind Deconvolution Approach for Radio Interferometry. Proc. IEEE Sensor Array and Multichannel Signal Process. Workshop (SAM), 475–479.
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6. Thouvenin, P.-A., Dobigeon, N., & Tourneret, J.-Y. (2017). Unmixing Multitemporal Hyperspectral Images Accounting for Smooth and Abrupt Variations. Proc. European Signal Process. Conf. (EUSIPCO), 2378–2383.
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7. Thouvenin, P.-A., Dobigeon, N., & Tourneret, J.-Y. (2016). Unmixing multitemporal hyperspectral images with variability: an online algorithm. Proc. IEEE Int. Conf. Acoust., Speech, and Signal Processing (ICASSP), 3351–3355.
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8. Thouvenin, P.-A., Dobigeon, N., & Tourneret, J.-Y. (2015). A Perturbed Linear Mixing Model Accounting for Spectral Variability. Proc. European Signal Process. Conf. (EUSIPCO), 819–823.
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Workshop and conference abstracts

1. Palud, P., Le Petit, F., Chainais, P., Thouvenin, P.-A., Bron, E., & the ORION B consortium. (2022, October). Inferring physical conditions in star forming regions with new Bayesian approach and spatial regularization. Proceedings of the “Physique Et Chimie Du Milieu Interstellaire” (PCMI) Conference.
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2. Palud, P., Bron, E., Thouvenin, P.-A., Le Petit, F., & Chainais, P. (2022). Sampler algorithm for non-convex inverse problem. 3rd IMA Conference on Inverse Problems from Theory to Application, 44.
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3. Thouvenin, P.-A., Repetti, A., & Chainais, P. (2022). Distributed sampling for imaging inverse problems in high dimension. 3rd IMA Conference on Inverse Problems from Theory to Application, 45.
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4. Palud, P., Le Petit, F., Chainais, P., Bron, E., & Thouvenin, P.-A. (2022, April). Dealing with uncertainty in millimeter astronomy: towards more realistic noise model and Bayesian approach. Multi-Line Diagnostics of the Interstellar Medium.
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5. Thouvenin, P.-A., Abdulaziz, A., Jiang, M., Dabbech, A., Repetti, A., Jackson, A., Thiran, J.-P., & Wiaux, Y. (2021, August). Parallel faceted imaging in radio interferometry via proximal splitting (Faceted HyperSARA). Proceedings of the XXXIVth URSI General Assembly (URSI GASS).
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National conferences

1. Einig, L., Palud, P., Chanussot, J., Pety, J., Bron, E., Chainais, P., Le Petit, F., Thouvenin, P.-A., Gerin, M., & Roueff, A. (2023, September). Réduction d’un modèle astrophysique par réseaux de neurones. Actes Du XXIXième Colloque GRETSI.
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2. Palud, P., Thouvenin, P.-A., Chainais, P., Bron, E., Le Petit, F., Beslic, I., Einig, L., Maria, M. G. S., Orkisz, J. H., Zakardjian, A., Bardeau, S., Chanussot, J., Gerin, M., Goicoechea, J. R., Gratier, P., Guzman, V. V., Levrier, F., Örberg, K., Peretto, N., … Hughes, A. (2023, September). Problèmes inverses et test bayésien d’adéquation du modèle. Actes Du XXIX Ième Colloque GRETSI.
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3. Palud, P., Chainais, P., Le Petit, F., Bron, E., Thouvenin, P.-A., Vono, M., Einig, L., Santa-Maria, M. G., Gaudel, M., Orkisz, J. H., de Souza Magalhaes, V., Bardeau, S., Gerin, M., Goicoechea, J. R., Gratier, P., Guzman, V. V., Kainulainen, J., Levrier, F., Peretto, N., … Sievers, A. (2022). Mélange de bruits et échantillonnage de posterior non log-concave. Actes Du XXVIIIième Colloque GRETSI, 705–708.
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4. Thouvenin, P.-A., Repetti, A., & Chainais, P. (2022). Un algorithme MCMC distribué pour la résolution de problèmes inverses de grande dimension. Actes Du XXVIIIième Colloque GRETSI, 697–700.
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5. Thouvenin, P.-A., Dobigeon, N., & Tourneret, J.-Y. (2017). Une approche distribuée asynchrone pour la factorisation en matrices non-négatives – application au démélange hyperspectral. Actes Du XXVIième Colloque GRETSI, 1065–1068.
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6. Thouvenin, P.-A., Dobigeon, N., & Tourneret, J.-Y. (2015). Estimation de variabilité pour le démélange non-supervisé d’images hyperspectrales. Actes Du XXVième Colloque GRETSI, 601–604.
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Thesis

1. Thouvenin, P.-A. (2017). Modeling spectral and temporal variabilities in hyperspectral image unmixing [Institut national polytechnique de Toulouse (INPT)].
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