Publications

  1. Variational Inference for Uncertain Optimal Transport via Sinkhorn Parametrization — preview ICML 2026

    Variational Inference for Uncertain Optimal Transport via Sinkhorn Parametrization

    Ananyapam De, Linus Bleistein, Anton Frederik Thielmann, Benjamin Säfken

    Forty-third International Conference on Machine Learning, 2026

  2. Fairness Constrained Sampling using Augmented Lagrangian Langevin Monte Carlo — preview EurIPS Workshop 2025

    Fairness Constrained Sampling using Augmented Lagrangian Langevin Monte Carlo

    Ananyapam De, Benjamin Säfken

    EurIPS 2025 Workshop on Unifying Perspectives on Learning Biases, 2025

  3. Your Model Is Not Neutral—It’s Just Well-Socialized — preview EurIPS Workshop 2025

    Your Model Is Not Neutral—It’s Just Well-Socialized

    Ananyapam De, Benjamin Säfken

    Unifying Perspectives on Learning Biases (UBLP), EurIPS Workshop, 2025

  4. The Myth of Robust Classes: How Shielding Skews Perceived Stability — preview ICCV Workshop 2025

    The Myth of Robust Classes: How Shielding Skews Perceived Stability

    Ananyapam De, Benjamin Säfken

    Explainable Computer Vision: Quo Vadis? (eXCV), ICCV Workshop, 2025 · Non-proceedings track

  5. NODE-GAMLSS: Interpretable Uncertainty Modelling via Deep Distributional Regression — preview NeurIPS Workshop 2024

    NODE-GAMLSS: Interpretable Uncertainty Modelling via Deep Distributional Regression

    Ananyapam De, Anton Frederik Thielmann, Benjamin Säfken

    NeurIPS 2024 Workshop on Bayesian Decision-making and Uncertainty, 2024

  6. Latent Factor Analysis and Regression of Multivariate Poisson via Amortized Variational Inference — preview MS Thesis 2023

    Latent Factor Analysis and Regression of Multivariate Poisson via Amortized Variational Inference

    Ananyapam De

    MS Thesis, 2023