Interpreting noisy data through a retrocausal lens begins by relaxing the assumption that causes must …
Tag:
Bayesian inference
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When people imagine how things could have turned out differently, they are engaging in counterfactual …
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In many practical implementations of Bayesian inference, the choice of prior is often treated as …
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In Bayesian inference, what are often called “priors” are better understood as structured anticipations about …
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Bayesian inference begins with the idea that uncertainty about unknown quantities is represented by probability …
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To formalize retrocausal inference, it is useful to start from standard probabilistic modeling and then …
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Accounts of conscious access rooted in global workspace theory have long emphasized a distinctive pattern …
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Human decision making often appears to unfold in a linear temporal sequence: information is gathered, …
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The notion of a two-state brain captures the idea that large-scale neural activity often settles …
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Time-symmetric cortical computation starts from the premise that neural dynamics in the cortex can be …
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