An innovative solution for breast cancer textual big data analysis. - Nicolas Thiebaut; Antoine Simoulin; Karl Neuberger; Issam Ibnouhsein; Nicolas Bousquet 002; Nathalie Reix; Sébastien Molière; Carole Mathelin (CoRR, 2017)

CounteRGAN: Generating Realistic Counterfactuals with Residual Generative Adversarial Nets. - Daniel Nemirovsky; Nicolas Thiebaut; Ye Xu; Abhishek Gupta (CoRR, 2020)

Providing Actionable Feedback in Hiring Marketplaces using Generative Adversarial Networks. - Daniel Nemirovsky; Nicolas Thiebaut; Ye Xu; Abhishek Gupta (WSDM, 2021)

CounteRGAN: Generating counterfactuals for real-time recourse and interpretability using residual GANs. - Daniel Nemirovsky; Nicolas Thiebaut; Ye Xu; Abhishek Gupta (UAI, 2022)

Learning Résumé Embeddings with Search Data and Transformers. - Jonathan Hourany; Aaron Zira; Ignacio Avas; Nicolas Thiebaut (SMC, 2023)

From free-text electronic health records to structured cohorts: Onconum, an innovative methodology for real-world data mining in breast cancer. - Antoine Simoulin; Nicolas Thiebaut; Karl Neuberger; Issam Ibnouhsein; Nicolas J.-B. Brunel; Raphaël Viné; Nicolas Bousquet 002; Jules Latapy; Nathalie Reix; Sébastien Molière; Massimo Lodi; Carole Mathelin (Comput. Methods Programs Biomed., 2023)

Diffusion Synthesizer for Efficient Multilingual Speech to Speech Translation. - Nameer Hirschkind; Xiao Yu; Mahesh Kumar Nandwana; Joseph Liu 001; Eloi du Bois; Dao Le; Nicolas Thiebaut; Colin Sinclair; Kyle Spence; Charles Shang; Zoë Abrams; Morgan McGuire (INTERSPEECH, 2024)