Sebastian Weichwald

According to our database1, Sebastian Weichwald authored at least 22 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
Adjustment Identification Distance: A gadjid for Causal Structure Learning.
CoRR, 2024

2023
Unfair Utilities and First Steps Towards Improving Them.
CoRR, 2023

Simple Sorting Criteria Help Find the Causal Order in Additive Noise Models.
CoRR, 2023

A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2021
Causality in Cognitive Neuroscience: Concepts, Challenges, and Distributional Robustness.
J. Cogn. Neurosci., 2021

Beware of the Simulated DAG! Varsortability in Additive Noise Models.
CoRR, 2021

Compositional abstraction error and a category of causal models.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning.
Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy to Game.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2019
Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise.
J. Mach. Learn. Res., 2019

Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values.
Proceedings of the NeurIPS 2019 Competition and Demonstration Track, 2019

2018
groupICA: Independent component analysis for grouped data.
CoRR, 2018

2017
Causal Consistency of Structural Equation Models.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Personalized brain-computer interface models for motor rehabilitation.
Proceedings of the 2017 IEEE International Conference on Systems, Man, and Cybernetics, 2017

2016
MERLiN: Mixture Effect Recovery in Linear Networks.
IEEE J. Sel. Top. Signal Process., 2016

Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation.
J. Mach. Learn. Res., 2016

Optimal Coding in Biological and Artificial Neural Networks.
CoRR, 2016

Pymanopt: A Python Toolbox for Manifold Optimization using Automatic Differentiation.
CoRR, 2016

Recovery of non-linear cause-effect relationships from linearly mixed neuroimaging data.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2016

2015
Causal interpretation rules for encoding and decoding models in neuroimaging.
NeuroImage, 2015

2014
Causal and anti-causal learning in pattern recognition for neuroimaging.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2014

Decoding index finger position from EEG using random forests.
Proceedings of the 4th International Workshop on Cognitive Information Processing, 2014


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