| 2025 | AISTATS | Bayesian Off-Policy Evaluation and Learning for Large Action Spaces. | Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba |
| 2025 | AISTATS | DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows. | Jonathan Geuter, Clment Bonet, Anna Korba, David Alvarez-Melis |
| 2025 | AISTATS | Implicit Diffusion: Efficient optimization through stochastic sampling. | Pierre Marion, Anna Korba, Peter L. Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-Lpez, Courtney Paquette, Quentin Berthet |
| 2025 | ICLR | Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics. | Omar Chehab, Anna Korba, Austin J. Stromme, Adrien Vacher |
| 2025 | ICML | Flowing Datasets with Wasserstein over Wasserstein Gradient Flows. | Clment Bonet, Christophe Vauthier, Anna Korba |
| 2025 | ICML | Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis. | Christophe Vauthier, Anna Korba, Quentin Mrigot |
| 2025 | ICML | Density Ratio Estimation with Conditional Probability Paths. | Hanlin Yu, Arto Klami, Aapo Hyvrinen, Anna Korba, Omar Chehab |
| 2024 | ICML | A connection between Tempering and Entropic Mirror Descent. | Nicolas Chopin, Francesca R. Crucinio, Anna Korba |
| 2024 | ICML | Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians. | Tom Huix, Anna Korba, Alain Oliviero Durmus, Eric Moulines |
| 2024 | UAI | Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling. | Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba |
| 2023 | ICLR | Sampling with Mollified Interaction Energy Descent. | Lingxiao Li, Qiang Liu, Anna Korba, Mikhail Yurochkin, Justin Solomon |
| 2023 | ICML | Exponential Smoothing for Off-Policy Learning. | Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba |
| 2022 | AISTATS | Adaptive Importance Sampling meets Mirror Descent : a Bias-variance Tradeoff. | Anna Korba, Franois Portier |
| 2022 | ICML | Accurate Quantization of Measures via Interacting Particle-based Optimization. | Lantian Xu, Anna Korba, Dejan Slepcev |
| 2021 | ICML | Kernel Stein Discrepancy Descent. | Anna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin |
| 2021 | ICML | Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction. | Afsaneh Mastouri, Yuchen Zhu, Limor Gultchin, Anna Korba, Ricardo Silva, Matt J. Kusner, Arthur Gretton, Krikamol Muandet |
| 2019 | ALT | Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach. | Mastane Achab, Anna Korba, Stphan Clmenon |
| 2018 | ALT | Ranking Median Regression: Learning to Order through Local Consensus. | Stphan Clmenon, Anna Korba, Eric Sibony |
| 2018 | ESANN | On aggregation in ranking median regression. | Stphan Clmenon, Anna Korba |
| 2017 | AISTATS | A Learning Theory of Ranking Aggregation. | Anna Korba, Stphan Clmenon, Eric Sibony |
| 2016 | ICML | Controlling the distance to a Kemeny consensus without computing it. | Yunlong Jiao, Anna Korba, Eric Sibony |