DECoVaC: Design of Experiments with Controlled Variability Components. - Thomas Boquet; Laure Delisle; Denis Kochetkov; Nathan Schucher; Parmida Atighehchian; Boris N. Oreshkin; Julien Cornebise (CoRR, 2019)

Synbols: Probing Learning Algorithms with Synthetic Datasets. - Alexandre Lacoste; Pau Rodríguez López; Frederic Branchaud-Charron; Parmida Atighehchian; Massimo Caccia; Issam Hadj Laradji; Alexandre Drouin; Matt Craddock; Laurent Charlin; David Vázquez 001 (NeurIPS, 2020)

Bayesian active learning for production, a systematic study and a reusable library. - Parmida Atighehchian; Frédéric Branchaud-Charron; Alexandre Lacoste (CoRR, 2020)

A Weakly Supervised Region-Based Active Learning Method for COVID-19 Segmentation in CT Images. - Issam H. Laradji; Pau Rodríguez; Frederic Branchaud-Charron; Keegan Lensink; Parmida Atighehchian; William Parker; David Vázquez 001; Derek Nowrouzezahrai (CoRR, 2020)

Can Active Learning Preemptively Mitigate Fairness Issues? - Frédéric Branchaud-Charron; Parmida Atighehchian; Pau Rodríguez; Grace Abuhamad; Alexandre Lacoste (CoRR, 2021)

Data Augmentation for Intent Classification with Off-the-shelf Large Language Models. - Gaurav Sahu; Pau Rodríguez; Issam H. Laradji; Parmida Atighehchian; David Vázquez 001; Dzmitry Bahdanau (ConvAI@ACL, 2022)

Structure and Content-Guided Video Synthesis with Diffusion Models. - Patrick Esser; Johnathan Chiu; Parmida Atighehchian; Jonathan Granskog; Anastasis Germanidis (ICCV, 2023)

Mitigating stereotypical biases in text to image generative systems. - Piero Esposito; Parmida Atighehchian; Anastasis Germanidis; Deepti Ghadiyaram (CoRR, 2023)

Stochastic Batch Acquisition: A Simple Baseline for Deep Active Learning. - Andreas Kirsch 002; Sebastian Farquhar; Parmida Atighehchian; Andrew Jesson; Frédéric Branchaud-Charron; Yarin Gal (Trans. Mach. Learn. Res., 2023)

Domain Adaptation of VLM for Soccer Video Understanding. - Tiancheng Jiang; Henry Wang; Md Sirajus Salekin; Parmida Atighehchian; Shinan Zhang (CVPR Workshops, 2025)