Exact correspondence between a Markov process and propagation on networks - Pierre-André Noël; Antoine Allard; Laurent Hébert-Dufresne; Vincent Marceau; Louis J. Dubé (CoRR, 2011)

Modeling the dynamical interaction between epidemics on overlay networks - Vincent Marceau; Pierre-André Noël; Laurent Hébert-Dufresne; Antoine Allard; Louis J. Dubé (CoRR, 2011)

Exact solution of bond percolation on small arbitrary graphs - Antoine Allard; Laurent Hébert-Dufresne; Pierre-André Noël; Vincent Marceau; Louis J. Dubé (CoRR, 2012)

Bond percolation on a class of correlated and clustered random graphs - Antoine Allard; Laurent Hébert-Dufresne; Pierre-André Noël; Vincent Marceau; Louis J. Dubé (CoRR, 2012)

Peeking into the invitation-based adoption process of OSN-based applications. - Mohammad Rezaur Rahman; Pierre-André Noël; Chen-Nee Chuah; Balachander Krishnamurthy; Raissa M. D'Souza; Shyhtsun Felix Wu (Comput. Commun. Rev., 2014)

Quantifying dynamical spillover in co-evolving multiplex networks. - Vikram Vijayaraghavan; Pierre-André Noël; Zeev Maoz; Raissa M. D'Souza (CoRR, 2015)

On the Value of ML Models. - Fabio Casati; Pierre-André Noël; Jie Yang 028 (CoRR, 2021)

Flaky Performances when Pretraining on Relational Databases. - Shengchao Liu; David Vázquez 001; Jian Tang 005; Pierre-André Noël (CoRR, 2022)

Flaky Performances When Pretraining on Relational Databases (Student Abstract). - Shengchao Liu; David Vázquez 001; Jian Tang 005; Pierre-André Noël (AAAI, 2023)

Constraining Representations Yields Models That Know What They Don't Know. - João Monteiro 002; Pau Rodríguez; Pierre-André Noël; Issam H. Laradji; David Vázquez 001 (ICLR, 2023)

XC-Cache: Cross-Attending to Cached Context for Efficient LLM Inference. - João Monteiro 002; Étienne Marcotte; Pierre-André Noël; Valentina Zantedeschi; David Vázquez 001; Nicolas Chapados; Christopher Pal; Perouz Taslakian (EMNLP (Findings), 2024)

RepLiQA: A Question-Answering Dataset for Benchmarking LLMs on Unseen Reference Content. - João Monteiro 002; Pierre-André Noël; Étienne Marcotte; Sai Rajeswar Mudumba; Valentina Zantedeschi; David Vázquez 001; Nicolas Chapados; Chris Pal; Perouz Taslakian (NeurIPS, 2024)

Expecting The Unexpected: Towards Broad Out-Of-Distribution Detection. - Charles Guille-Escuret; Pierre-André Noël; Ioannis Mitliagkas; David Vázquez 001; João Monteiro 002 (NeurIPS, 2024)

BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks. - Juan A. Rodríguez; Xiangru Jian; Siba Smarak Panigrahi; Tianyu Zhang; Aarash Feizi; Abhay Puri; Akshay Kalkunte; François Savard; Ahmed Masry; Shravan Nayak; Rabiul Awal; Mahsa Massoud; et al. (CoRR, 2024)

BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks. - Juan A. Rodríguez; Xiangru Jian; Siba Smarak Panigrahi; Tianyu Zhang; Aarash Feizi; Abhay Puri; Akshay Kalkunte Suresh; François Savard; Ahmed Masry; Shravan Nayak; Rabiul Awal; Mahsa Massoud; et al. (ICLR, 2025)

AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Understanding. - Ahmed Masry; Juan A. Rodríguez; Tianyu Zhang; Suyuchen Wang; Chao Wang; Aarash Feizi; Akshay Kalkunte Suresh; Abhay Puri; Xiangru Jian; Pierre-André Noël; Sathwik Tejaswi Madhusudhan; Marco Pedersoli; et al. (CoRR, 2025)

Unifying Autoregressive and Diffusion-Based Sequence Generation. - Nima Fathi; Torsten Scholak; Pierre-André Noël (CoRR, 2025)

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion. - Frederick Shpilevskiy; Saiyue Lyu; Krishnamurthy Dj Dvijotham; Mathias Lécuyer; Pierre-André Noël (CoRR, 2025)