Results 231 to 240 of about 22,053,960 (269)

The self as destination or illusion: a comparative study of individuation in Jung and self-transcendence in Buddhist Vijñānavāda. [PDF]

Front Psychol
Zhang Y.
europepmc   +1 more source

The silent influence: experimental validation of cultural unconscious and its psychological impact through Chinese archetypal imagery. [PDF]

Front Psychol
Wang W, Shen H, Zhang X, Wen L.
europepmc   +1 more source

Functional archetypes in the human gut microbiome reveal metabolic diversity, stability, and influence disease-associated signatures. [PDF]

Microbiome
Meawad M, Singh D, Deng A, Sonthalia R, Cai E, Dumeaux V.   +5 more
europepmc   +1 more source

U-Net-based reactive center loop-identifier for serpins. [PDF]

Bioinform Adv
Liang J, Wang C, Zhou L.
europepmc   +1 more source

ArchetypeShift: An R Package Integrating KEGG-Informed Pathway Analysis and IPA-Derived Functional Predictions for Validation of Single-Cell Archetypes. [PDF]

Bioinform Biol Insights
Wilson AP, Chaaban H, Burge KY.
europepmc   +1 more source

Archetypal Analysis of Interval Data.

Reliab. Comput., 2010
In this paper we present a mathematical model for archetypal analysis of data represented by means of intervals of real numbers. We extend the model for single-valued data proposed in the pioneering work of Cutler and Breiman on this topic. The core problem is a non-convex optimization one, which we solve by means of a sequential quadratic programming ...
S. Corsaro, MARINO, MARINA
openaire   +4 more sources

Archetypal analysis for data‐driven prototype identification

Statistical Analysis and Data Mining: The ASA Data Science Journal, 2016
Prototypes, as Rosch (1973) defined the term in the cognitive sciences field, are ideal exemplars that summarize and represent groups of objects (or categories) and that are “typical" according to their internal resemblance and external dissimilarityvis‐à‐visother groups or categories.
RAGOZINI, GIANCARLO, PALUMBO, FRANCESCO, D'Esposito M. R.   +2 more
openaire   +6 more sources

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Archetypical motion: Supervised game behavior learning with Archetypal Analysis

2013 IEEE Conference on Computational Inteligence in Games (CIG), 2013
The problem of creating believable game AI poses numerous challenges for computational intelligence research. A particular challenge consists in creating human-like behaving game bots by means of applying machine learning to game-play data recorded by human players.
Rafet Sifa, Christian Bauckhage
openaire   +2 more sources