What is recorded here?
Conditioned a neural value model on sampled quantile fractions to approximate return quantile functions, supporting distributional learning and distorted-quantile risk-sensitive action evaluation.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Extends QR-DQN rather than inventing distributional RL or quantile regression. Finite-capacity stochastic quantile sampling is not exact representation of arbitrary return laws; risk-distortion experiments do not establish universally optimal risk-sensitive control or neural convergence.
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People and systems
Will Dabney; Georg Ostrovski; David Silver; Rémi Munos
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
Implicit Quantile Networks: sampled quantile-function value models
Conditioned a neural value model on sampled quantile fractions to approximate return quantile functions, supporting distributional learning and distorted-quantile risk-sensitive action evaluation.
Scientific scope
Extends QR-DQN rather than inventing distributional RL or quantile regression. Finite-capacity stochastic quantile sampling is not exact representation of arbitrary return laws; risk-distortion experiments do not establish universally optimal risk-sensitive control or neural convergence.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Will Dabney; Georg Ostrovski; David Silver; Rémi Munos
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.