Zobrazeno 1 - 10
of 366
pro vyhledávání: '"Thams, P."'
We give a method for proactively identifying small, plausible shifts in distribution which lead to large differences in model performance. These shifts are defined via parametric changes in the causal mechanisms of observed variables, where constrain
Externí odkaz:
http://arxiv.org/abs/2205.15947
Autor:
Daria Antonenko, Anna Elisabeth Fromm, Friederike Thams, Anna Kuzmina, Malte Backhaus, Elena Knochenhauer, Shu-Chen Li, Ulrike Grittner, Agnes Flöel
Publikováno v:
Alzheimer’s Research & Therapy, Vol 16, Iss 1, Pp 1-13 (2024)
Abstract Background Repeated sessions of training and non-invasive brain stimulation have the potential to enhance cognition in patients with cognitive impairment. We hypothesized that combining cognitive training with anodal transcranial direct curr
Externí odkaz:
https://doaj.org/article/1ca6a8754f1542ca97d7c11de95ddc69
Instrumental variable (IV) regression relies on instruments to infer causal effects from observational data with unobserved confounding. We consider IV regression in time series models, such as vector auto-regressive (VAR) processes. Direct applicati
Externí odkaz:
http://arxiv.org/abs/2203.06056
Recently, methods have been proposed that exploit the invariance of prediction models with respect to changing environments to infer subsets of the causal parents of a response variable. If the environments influence only few of the underlying mechan
Externí odkaz:
http://arxiv.org/abs/2202.00913
Autor:
Thams, Nikolaj, Hansen, Niels Richard
Constraint based causal structure learning for point processes require empirical tests of local independence. Existing tests require strong model assumptions, e.g. that the true data generating model is a Hawkes process with no latent confounders. Ev
Externí odkaz:
http://arxiv.org/abs/2110.12709
Contextual bandit and reinforcement learning algorithms have been successfully used in various interactive learning systems such as online advertising, recommender systems, and dynamic pricing. However, they have yet to be widely adopted in high-stak
Externí odkaz:
http://arxiv.org/abs/2106.00808
In this work, we introduce statistical testing under distributional shifts. We are interested in the hypothesis $P^* \in H_0$ for a target distribution $P^*$, but observe data from a different distribution $Q^*$. We assume that $P^*$ is related to $Q
Externí odkaz:
http://arxiv.org/abs/2105.10821
We propose a method for learning linear models whose predictive performance is robust to causal interventions on unobserved variables, when noisy proxies of those variables are available. Our approach takes the form of a regularization term that trad
Externí odkaz:
http://arxiv.org/abs/2103.02477
Autor:
Caroline Lindblad, Susanne Neumann, Sólrún Kolbeinsdóttir, Vasilios Zachariadis, Eric P. Thelin, Martin Enge, Sebastian Thams, Lou Brundin, Mikael Svensson
Publikováno v:
Journal of Inflammation, Vol 20, Iss 1, Pp 1-18 (2023)
Abstract Background Astrocytes respond to injury and disease through a process known as reactive astrogliosis, of which inflammatory signaling is one subset. This inflammatory response is heterogeneous with respect to the inductive stimuli and the af
Externí odkaz:
https://doaj.org/article/8b39860ab2eb440491d850d45468a07a
Autor:
Daria Antonenko, Anna Elisabeth Fromm, Friederike Thams, Ulrike Grittner, Marcus Meinzer, Agnes Flöel
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-13 (2023)
Abstract The combination of repeated behavioral training with transcranial direct current stimulation (tDCS) holds promise to exert beneficial effects on brain function beyond the trained task. However, little is known about the underlying mechanisms
Externí odkaz:
https://doaj.org/article/2c00d770d1ca456188327b675c8d3f30