Papers

Preprints and submissions

  1. Chewi, S., Pooladian, A-A., and Zhang, M. “Stability of the Kim—Milman flow map” arXiv PDF bib
  2. Ghafourpour, L., Chewi, S., Figalli, A., and Pooladian, A-A. “Variational inference via radial transport”
  3. Pooladian, A-A., and Niles-Weed, J. “Entropic estimation of optimal transport maps” (Best paper award at OTML NeurIPS workshop; 2021) arXiv PDF bib

Journal articles

  1. Jiang, Y., Chewi, S., and Pooladian, A-A. (supervisory role) “Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space”, Foundations of Computational Mathematics (2025+) arXiv PDF Slides bib
  2. Pooladian, A-A., and Niles-Weed, J. “Plug-in estimation of Schrödinger bridges”, SIAM Journal on Mathematics of Data Science (2025+) arXiv PDF bib
  3. Divol, V., Niles-Weed, J., and Pooladian, A-A. (alphabetical) “Tight stability for entropic Brenier maps”, International Mathematics Research Notices (2025+) arXiv PDF bib
  4. Divol, V., Niles-Weed, J., and Pooladian, A-A. (alphabetical) “Optimal transport map estimation in general function spaces”, Annals of Statistics (2025+) arXiv PDF Slides bib
  5. Chewi, S., and Pooladian, A-A. (alphabetical) “An entropic generalization of Caffarelli's contraction theorem via covariance inequalities”, Comptes Rendus Mathématique (2023) arXiv PDF Slides bib
  6. Domingo-Enrich, C., and Pooladian, A-A. (alphabetical) “An Explicit Expansion of the Kullback—Leibler Divergence along its Fisher-Rao gradient flow”, Transactions on Machine Learning Research (2023) arXiv PDF bib

Conference papers

  1. Haviv, D.* , Pooladian, A-A.* , Pe'er, D., and Amos, B. (Joint first author) “Wasserstein Flow Matching: Generative modeling over families of distributions”, 41st International Conference on Machine Learning (ICML 2025) arXiv PDF bib
  2. Baptista, R.* , Pooladian, A-A.* , Brennan, M., Marzouk Y., and Niles-Weed, J. (Joint first author) “Conditional simulation via entropic optimal transport: Toward non-parametric estimation of conditional Brenier maps”, 28th International Conference on Artificial Intelligence and Statistics (AISTATS 2025) arXiv PDF bib
  3. Kassraie, P., Pooladian, A-A., Klein, M., Thornton, J., Niles-Weed, J., and Cuturi, M. “Progressive Entropic Optimal Transport Solvers”, 38th Conference on Neural Information Processing Systems (NeurIPS 2024) arXiv PDF bib
  4. Klein, M., Pooladian, A-A., Ablin, P., Ndiaye, E., Niles-Weed, J., and Cuturi, M. “Learning Costs for Structured Monge Displacements”, 38th Conference on Neural Information Processing Systems (NeurIPS 2024) arXiv PDF bib
  5. Jiang, Y., Chewi, S., and Pooladian, A-A. (Supervisory role) “Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space”, extended abstract in the 37th Conference on Learning Theory (COLT 2024) arXiv PDF Slides bib
  6. Pooladian, A-A., Domingo-Enrich, C., Chen R., and Amos, B. “Neural Optimal Transport with Lagrangian Costs”, 40th International Conference on Uncertainty in Artificial Intelligence (UAI 2024) PDF bib
  7. Pooladian, A-A.* , Divol, V.* , and Niles-Weed, J. (Joint first author) “Minimax estimation of discontinuous optimal transport maps: The semi-discrete case”, 40th International Conference on Machine Learning (ICML 2023) arXiv PDF Slides bib
  8. Pooladian, A-A.* , Ben-Hamu, H.* , Domingo-Enrich, C.* , Amos, B., Lipman, Y., and Chen, R. (Joint first author) “Multisample Flow Matching: Straightening Flows with Minibatch Couplings”, 40th International Conference on Machine Learning (ICML 2023) arXiv PDF bib
  9. Pooladian, A-A., Cuturi, M., and Niles-Weed, J. “Debiaser Beware: Pitfalls of Centering Regularized Transport maps”, 39th International Conference on Machine Learning (ICML 2022) arXiv PDF Slides bib

pre-PhD conference, journal, and workshop papers

  1. Finlay, C., Gerolin, A., Oberman, A., Pooladian A-A. (alphabetical) “Learning normalizing flows from Entropy-Kantorovich potentials”, Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models (ICML 2020 workshop), with contributing talk arXiv PDF bib
  2. Hoheisel, T., Pablos, B., Pooladian, A-A., Schwartz, A., and Steverango, L. (alphabetical) “A study of one-parameter regularizations for mathematical programs with vanishing constraints”, Optimization Methods and Software (2020) arXiv PDF bib
  3. Pooladian, A-A., Finlay, C., Hoheisel, T., and Oberman, A. “A principled approach for generating adversarial images under non-smooth dissimilarity metrics”, 23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020) arXiv PDF bib
  4. Finlay, C., Pooladian, A-A., and Oberman, A. “The LogBarrier Adversarial Attack: Making effective use of decision boundary information”, IEEE International Conference on Computer Vision (ICCV 2019) arXiv PDF bib