The Wasserstein Distance as a Dissimilarity Measure for Mass Spectra with Application to Spectral Deconvolution. - Szymon Majewski; Michal Aleksander Ciach; Michal Startek; Wanda Niemyska; Blazej Miasojedow; Anna Gambin (WABI, 2018)

Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions. - Umut Simsekli; Antoine Liutkus; Szymon Majewski; Alain Durmus (CoRR, 2018)

Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions. - Antoine Liutkus; Umut Simsekli; Szymon Majewski; Alain Durmus; Fabian-Robert Stöter (ICML, 2019)

Analysis of Langevin Monte Carlo via Convex Optimization. - Alain Durmus; Szymon Majewski; Blazej Miasojedow (J. Mach. Learn. Res., 2019)

Kernel Stein Discrepancy Descent. - Anna Korba; Pierre-Cyril Aubin-Frankowski; Szymon Majewski; Pierre Ablin (ICML, 2021)

Minibatch optimal transport distances; analysis and applications. - Kilian Fatras; Younes Zine; Szymon Majewski; Rémi Flamary; Rémi Gribonval; Nicolas Courty (CoRR, 2021)

Variational Inference of overparameterized Bayesian Neural Networks: a theoretical and empirical study. - Tom Huix; Szymon Majewski; Alain Durmus; Eric Moulines; Anna Korba (CoRR, 2022)

Adaptive Bayesian SLOPE: Model Selection With Incomplete Data. - Wei Jiang 027; Malgorzata Bogdan; Julie Josse; Szymon Majewski; Blazej Miasojedow; Veronika Rocková (J. Comput. Graph. Stat., 2022)