Sequence Disambiguation with Synaptic Traces in Associative Neural Networks. - Ramon H. Martinez; Oskar Kviman; Anders Lansner; Pawel Andrzej Herman (ICANN (1), 2019)

Multiple Importance Sampling ELBO and Deep Ensembles of Variational Approximations. - Oskar Kviman; Harald Melin; Hazal Koptagel; Victor Elvira; Jens Lagergren (AISTATS, 2022)

VaiPhy: a Variational Inference Based Algorithm for Phylogeny. - Hazal Koptagel; Oskar Kviman; Harald Melin; Negar Safinianaini; Jens Lagergren (NeurIPS, 2022)

Learning with MISELBO: The Mixture Cookbook. - Oskar Kviman; Ricky Molén; Alexandra Hotti; Semih Kurt; Víctor Elvira; Jens Lagergren (CoRR, 2022)

Statistical Distance Based Deterministic Offspring Selection in SMC Methods. - Oskar Kviman; Hazal Koptagel; Harald Melin; Jens Lagergren (CoRR, 2022)

Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational Autoencoders. - Oskar Kviman; Ricky Molén; Alexandra Hotti; Semih Kurt; Víctor Elvira; Jens Lagergren (ICML, 2023)

Variational Resampling. - Oskar Kviman; Nicola Branchini; Víctor Elvira; Jens Lagergren (AISTATS, 2024)

Efficient Mixture Learning in Black-Box Variational Inference. - Alexandra Hotti; Oskar Kviman; Ricky Molén; Víctor Elvira; Jens Lagergren (ICML, 2024)

Indirectly Parameterized Concrete Autoencoders. - Alfred Nilsson; Klas Wijk; Sai Bharath Chandra Gutha; Erik Englesson; Alexandra Hotti; Carlo Saccardi; Oskar Kviman; Jens Lagergren; Ricardo Vinuesa; Hossein Azizpour (ICML, 2024)

Improved Variational Bayesian Phylogenetic Inference using Mixtures. - Ricky Molén; Oskar Kviman; Jens Lagergren (Trans. Mach. Learn. Res., 2024)