| 2025 | ICLR | Continuous Ensemble Weather Forecasting with Diffusion models. | Martin Andrae, Tomas Landelius, Joel Oskarsson, Fredrik Lindsten |
| 2025 | ICLR | cryoSPHERE: Single-Particle HEterogeneous REconstruction from cryo EM. | Gabriel Ducrocq, Lukas Grunewald, Sebastian Westenhoff, Fredrik Lindsten |
| 2025 | ICML | Solving Linear-Gaussian Bayesian Inverse Problems with Decoupled Diffusion Sequential Monte Carlo. | Filip Ekstrm Kelvinius, Zheng Zhao, Fredrik Lindsten |
| 2025 | ICML | WyckoffDiff - A Generative Diffusion Model for Crystal Symmetry. | Filip Ekstrm Kelvinius, Oskar B. Andersson, Abhijith S. Parackal, Dong Qian, Rickard Armiento, Fredrik Lindsten |
| 2025 | UAI | Discriminative ordering through ensemble consensus. | Louis Ohl, Fredrik Lindsten |
| 2024 | AISTATS | Unsupervised Novelty Detection in Pretrained Representation Space with Locally Adapted Likelihood Ratio. | Amirhossein Ahmadian, Yifan Ding, Gabriel Eilertsen, Fredrik Lindsten |
| 2024 | AISTATS | Discriminator Guidance for Autoregressive Diffusion Models. | Filip Ekstrm Kelvinius, Fredrik Lindsten |
| 2024 | AISTATS | On the connection between Noise-Contrastive Estimation and Contrastive Divergence. | Amanda Olmin, Jakob Lindqvist, Lennart Svensson, Fredrik Lindsten |
| 2024 | BMVC | On Partial Prototype Collapse in the DINO Family of Self-Supervised Methods. | Hariprasath Govindarajan, Per Sidn, Jacob Roll, Fredrik Lindsten |
| 2023 | AISTATS | Temporal Graph Neural Networks for Irregular Data. | Joel Oskarsson, Per Sidn, Fredrik Lindsten |
| 2023 | ICASSP | Enhancing Representation Learning with Deep Classifiers in Presence of Shortcut. | Amirhossein Ahmadian, Fredrik Lindsten |
| 2023 | ICLR | DINO as a von Mises-Fisher mixture model. | Hariprasath Govindarajan, Per Sidn, Jacob Roll, Fredrik Lindsten |
| 2023 | UAI | Fast and scalable score-based kernel calibration tests. | Pierre Glaser, David Widmann, Fredrik Lindsten, Arthur Gretton |
| 2022 | AISTATS | Robustness and Reliability When Training With Noisy Labels. | Amanda Olmin, Fredrik Lindsten |
| 2022 | ICML | Scalable Deep Gaussian Markov Random Fields for General Graphs. | Joel Oskarsson, Per Sidn, Fredrik Lindsten |
| 2022 | ICONIP | Active Learning with Weak Supervision for Gaussian Processes. | Amanda Olmin, Jakob Lindqvist, Lennart Svensson, Fredrik Lindsten |
| 2021 | ICLR | Calibration tests beyond classification. | David Widmann, Fredrik Lindsten, Dave Zachariah |
| 2021 | IJCAI | Likelihood-free Out-of-Distribution Detection with Invertible Generative Models. | Amirhossein Ahmadian, Fredrik Lindsten |
| 2020 | ICASSP | Particle Filter with Rejection Control and Unbiased Estimator of the Marginal Likelihood. | Jan Kudlicka, Lawrence M. Murray, Thomas B. Schn, Fredrik Lindsten |
| 2020 | ICML | Deep Gaussian Markov Random Fields. | Per Sidn, Fredrik Lindsten |
| 2019 | AISTATS | Evaluating model calibration in classification. | Juozas Vaicenavicius, David Widmann, Carl R. Andersson, Fredrik Lindsten, Jacob Roll, Thomas B. Schn |
| 2016 | ICML | Interacting Particle Markov Chain Monte Carlo. | Tom Rainforth, Christian A. Naesseth, Fredrik Lindsten, Brooks Paige, Jan-Willem van de Meent, Arnaud Doucet, Frank D. Wood |
| 2015 | AISTATS | Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering. | Simon Lacoste-Julien, Fredrik Lindsten, Francis R. Bach |
| 2015 | ICASSP | Particle Gibbs with refreshed backward simulation. | Pete Bunch, Fredrik Lindsten, Sumeetpal S. Singh |
| 2015 | ICML | Nested Sequential Monte Carlo Methods. | Christian A. Naesseth, Fredrik Lindsten, Thomas B. Schn |
| 2014 | ITW | Capacity estimation of two-dimensional channels using Sequential Monte Carlo. | Christian A. Naesseth, Fredrik Lindsten, Thomas B. Schn |
| 2013 | ICASSP | Particle metropolis hastings using Langevin dynamics. | Johan Dahlin, Fredrik Lindsten, Thomas B. Schn |
| 2013 | ICASSP | An efficient stochastic approximation EM algorithm using conditional particle filters. | Fredrik Lindsten |
| 2013 | ICASSP | Rao-Blackwellized particle smoothers for mixed linear/nonlinear state-space models. | Fredrik Lindsten, Pete Bunch, Simon J. Godsill, Thomas B. Schn |
| 2013 | ICASSP | Adaptive stopping for fast particle smoothing. | Ehsan Taghavi, Fredrik Lindsten, Lennart Svensson, Thomas B. Schn |
| 2012 | ICASSP | On the use of backward simulation in the particle Gibbs sampler. | Fredrik Lindsten, Thomas B. Schn |
| 2010 | ICRA | Geo-referencing for UAV navigation using environmental classification. | Fredrik Lindsten, Jonas Callmer, Henrik Ohlsson, David Trnqvist, Thomas B. Schn, Fredrik Gustafsson |