de Vignemont, F. (2023). Désenchanter le corps.
de Vignemont, F. (2023). Affective bodily awareness.
Proust, J. (2021). Penser vite ou penser bien ? Odile Jacob
Beran, M., Brandl, J., Perner, J. & Proust, J. (2012). The Foundations of Metacognition.
Bouvier, A. (2009). Joint Commitment, Coercion and Freedom in Science : Conceptual Analysis and Case Studies. , 143–61
Dokic, J. & Proust, J. (2002). Simulation and Knowledge of Action.
Gutkin, B. & Ahmed, S. (2012). Computational Neuroscience of Drug Addiction.
Imbert, M. (2020). La fin du regard éclairant. Une révolution dans les sciences de la vision au XIè siècle, Ibn al-Haytham.
Le Coënt, A., Fribourg, L., Vacher, J. & Wisniewski, R. (2020). Probabilistic reachability and control synthesis for stochastic switched systems using the tamed Euler method. Nonlinear Analysis: Hybrid Systems, 36, 100860Elsevier. doi:10.1016/j.nahs.2020.100860
Lebreton, M. & Palminteri, S. (2016). When are inter-individual brain-behavior correlations informative? bioRxiv. doi:10.1101/036772
Neri, P. (2018). Classification images as descriptive statistics. "Journal of Mathematical Psychology", "82"("1), "26–37"
Origgi, G. (2019). Reputation: What it is and why it Matters. Princeton University Press
Origgi, G. (2019). Passions Sociales. Paris: PUF
Origgi, G. (2018). South, Status and Knowledge: Epistemic Dominance and Forms of Epistemic Injustice.
Origgi, G. (2018). https://www.openaire.eu.
Origgi, G. (2018). Rapport éthique du projet Openair.
Origgi, G. (2018). Rapports du working group ALLEA Trust, Truth and Expertise.
Origgi, G. (2018). Reputation. What it is and Why it matters. Princeton University Press
Proust, J. & Fortier, M. (2018). Metacognitive Diversity - An Interdisciplinary approaches. Oxford: Oxford University Press
Proust, J. (2013). The Philosophy of Metacognition: Mental Agency and Self-Awareness.
Proust, J. (2017). Non-human Metacognition.
Ting, C. , Palminteri, S., Engelmann, J. & Lebreton, M. (2019). Decreased confidence in loss-avoidance contexts is a primary meta-cognitive bias of human reinforcement learning. bioRxiv. doi:10.1101/593368
Vacher, J. , Davila, A., Kohn, A. & Coen-Cagli, R. (2020). Texture Interpolation for Probing Visual Perception. Advances in Neural Information Processing Systems (Spotlight – top 5%)
Mamassian, P. & Coen-Cagli, R. (2018). An Ideal Observer Model to Probe Human Visual Segmentation of Natural Images. arXiv
