Sotabase

Career

· Assistant Professor, University of Amsterdam2018–
· MSc in Applied Physics and Electrical Engineering - International, Linköping University2013–
· PhD Student, Linköping University2013–2018
· Teaching Assistant, Linköping University2013–
· Research Assistant, Linköping University2012–
· BSc in Applied Mathematics and Machine Learning, Linköping University2007–2012
· Postdoctoral Research Scientist, Columbia University

Publications (49)

Variational Sequential Monte Carlo
International Conference on Artificial Intelligence and Statistics · 2017
229
cited
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
Neural Information Processing Systems · 2023
167
cited
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms
International Conference on Artificial Intelligence and Statistics · 2016
120
cited
Elements of Sequential Monte Carlo
Found. Trends Mach. Learn. · 2019
107
cited
Nested Sequential Monte Carlo Methods
International Conference on Machine Learning · 2015
86
cited
Sequential Monte Carlo Methods for System Identification
2015
82
cited
Markovian Score Climbing: Variational Inference with KL(p||q)
Neural Information Processing Systems · 2020
59
cited
Sequential Monte Carlo for Graphical Models
Neural Information Processing Systems · 2014
49
cited
Divide-and-Conquer With Sequential Monte Carlo
2014
45
cited
Variational Flow Matching for Graph Generation
Neural Information Processing Systems · 2024
43
cited
A Variational Perspective on Generative Flow Networks
Trans. Mach. Learn. Res. · 2022
41
cited
Interacting Particle Markov Chain Monte Carlo
International Conference on Machine Learning · 2016
34
cited
Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling
Neural Information Processing Systems · 2024
31
cited
High-Dimensional Filtering Using Nested Sequential Monte Carlo
IEEE Transactions on Signal Processing · 2016
28
cited
Equivariant Neural Diffusion for Molecule Generation
Neural Information Processing Systems · 2025
22
cited
Variational Combinatorial Sequential Monte Carlo Methods for Bayesian Phylogenetic Inference
Conference on Uncertainty in Artificial Intelligence · 2021
17
cited
Neural Diffusion Models
International Conference on Machine Learning · 2023
16
cited
Fast yet Safe: Early-Exiting with Risk Control
Neural Information Processing Systems · 2024
15
cited
E-Valuating Classifier Two-Sample Tests
Trans. Mach. Learn. Res. · 2022
14
cited
Rejection Sampling Variational Inference
2016
9
cited
Sotabase