Zobrazeno 1 - 10
of 128
pro vyhledávání: '"Hoel, Erik"'
Autor:
Comolatti, Renzo, Hoel, Erik
Causal emergence is the theory that macroscales can reduce the noise in causal relationships, leading to stronger causes at the macroscale. First identified using the effective information and later the integrated information in model systems, causal
Externí odkaz:
http://arxiv.org/abs/2202.01854
Autor:
Varley, Thomas, Hoel, Erik
Is reduction always a good scientific strategy? Does it always lead to a gain in information? The very existence of the special sciences above and beyond physics seems to hint no. Previous research has shown that dimension reduction (macroscales) can
Externí odkaz:
http://arxiv.org/abs/2104.13368
Deep Neural Networks (DNNs) are often examined at the level of their response to input, such as analyzing the mutual information between nodes and data sets. Yet DNNs can also be examined at the level of causation, exploring "what does what" within t
Externí odkaz:
http://arxiv.org/abs/2010.13871
Autor:
Chvykov, Pavel, Hoel, Erik
Publikováno v:
Causal Geometry. Entropy, 23(1), 24 (2021)
Information geometry has offered a way to formally study the efficacy of scientific models by quantifying the impact of model parameters on the predicted effects. However, there has been little formal investigation of causation in this framework, des
Externí odkaz:
http://arxiv.org/abs/2010.09390
Autor:
Hoel, Erik
Understanding of the evolved biological function of sleep has advanced considerably in the past decade. However, no equivalent understanding of dreams has emerged. Contemporary neuroscientific theories generally view dreams as epiphenomena, and the f
Externí odkaz:
http://arxiv.org/abs/2007.09560
Autor:
Kleiner, Johannes, Hoel, Erik
The search for a scientific theory of consciousness should result in theories that are falsifiable. However, here we show that falsification is especially problematic for theories of consciousness. We formally describe the standard experimental setup
Externí odkaz:
http://arxiv.org/abs/2004.03541
All networks can be analyzed at multiple scales. A higher scale of a network is made up of macro-nodes: subgraphs that have been grouped into individual nodes. Recasting a network at higher scales can have useful effects, such as decreasing the uncer
Externí odkaz:
http://arxiv.org/abs/1908.07565
Autor:
Klein, Brennan, Hoel, Erik
The connectivity of a network contains information about the relationships between nodes, which can denote interactions, associations, or dependencies. We show that this information can be analyzed by measuring the uncertainty (and certainty) contain
Externí odkaz:
http://arxiv.org/abs/1907.03902