Niklas Wahlström

24 papers Journal 19Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
Simultaneous State Estimation and Online Model Learning in a Soft Robotic System.
CoRR
Jan-Hendrik Ewering, Max Bartholdt, Simon F. G. Ehlers, Niklas Wahlström, Thomas B. Schön, Thomas Seel
2025 J jnl
Learning Dynamics from Input-Output Data with Hamiltonian Gaussian Processes.
CoRR
Jan-Hendrik Ewering, Robin E. Herrmann, Niklas Wahlström, Thomas B. Schön, Thomas Seel
2025 J jnl
Repulsive Ensembles for Bayesian Inference in Physics-informed Neural Networks.
CoRR
Philipp Pilar, Markus Heinonen, Niklas Wahlström
2024 — conf
Physics-informed neural networks with unknown measurement noise.
L4DC
Philipp Pilar, Niklas Wahlström
2024 J jnl
Probabilistic Matching of Real and Generated Data Statistics in Generative Adversarial Networks.
Trans. Mach. Learn. Res.
Philipp Pilar, Niklas Wahlström
2023 J jnl
Invertible Kernel PCA With Random Fourier Features.
IEEE Signal Process. Lett.
Daniel Gedon, Antônio H. Ribeiro, Niklas Wahlström, Thomas B. Schön
2023 J jnl
Invertible Kernel PCA with Random Fourier Features.
CoRR
Daniel Gedon, Antônio H. Ribeiro, Niklas Wahlström, Thomas B. Schön
2023 J jnl
Probabilistic matching of real and generated data statistics in generative adversarial networks.
CoRR
Philipp Pilar, Niklas Wahlström
2022 J jnl
Incorporating Sum Constraints into Multitask Gaussian Processes.
CoRR
Philipp Pilar, Carl Jidling, Thomas B. Schön, Niklas Wahlström
2022 J jnl
Incorporating Sum Constraints into Multitask Gaussian Processes.
Trans. Mach. Learn. Res.
Philipp Pilar, Carl Jidling, Thomas B. Schön, Niklas Wahlström
2022 J jnl
Physics-informed neural networks with unknown measurement noise.
CoRR
Philipp Pilar, Niklas Wahlström
2021 — conf
First Steps Towards Self-Supervised Pretraining of the 12-Lead ECG.
CinC
Daniel Gedon, Antônio H. Ribeiro, Niklas Wahlström, Thomas B. Schön
2021 J jnl
Learning deep autoregressive models for hierarchical data.
CoRR
Carl R. Andersson, Niklas Wahlström, Thomas B. Schön
2020 J jnl
Deep State Space Models for Nonlinear System Identification.
CoRR
Daniel Gedon, Niklas Wahlström, Thomas B. Schön, Lennart Ljung
2019 — conf
Deep Convolutional Networks in System Identification.
CDC
Carl R. Andersson, Antônio H. Ribeiro, Koen Tiels, Niklas Wahlström, Thomas B. Schön
2019 J jnl
Deep Convolutional Networks in System Identification.
CoRR
Carl R. Andersson, Antônio H. Ribeiro, Koen Tiels, Niklas Wahlström, Thomas B. Schön
2018 J jnl
Data-Driven Impulse Response Regularization via Deep Learning.
CoRR
Carl R. Andersson, Niklas Wahlström, Thomas B. Schön
2018 J jnl
Probabilistic approach to limited-data computed tomography reconstruction.
CoRR
Zenith Purisha, Carl Jidling, Niklas Wahlström, Simo Särkkä, Thomas B. Schön
2017 — conf
Linearly constrained Gaussian processes.
NIPS
Carl Jidling, Niklas Wahlström, Adrian Wills, Thomas B. Schön
2015 J jnl
Data-Efficient Learning of Feedback Policies from Image Pixels using Deep Dynamical Models.
CoRR
John-Alexander M. Assael, Niklas Wahlström, Thomas B. Schön, Marc Peter Deisenroth
2015 J jnl
From Pixels to Torques: Policy Learning with Deep Dynamical Models.
CoRR
Niklas Wahlström, Thomas B. Schön, Marc Peter Deisenroth
2015 J jnl
Modeling and interpolation of the ambient magnetic field by Gaussian processes.
CoRR
Arno Solin, Manon Kok, Niklas Wahlström, Thomas B. Schön, Simo Särkkä
2015 — —
Modeling of Magnetic Fields and Extended Objects for Localization Applications.
Niklas Wahlström
2014 J jnl
Learning deep dynamical models from image pixels.
CoRR
Niklas Wahlström, Thomas B. Schön, Marc Peter Deisenroth