These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

145 related articles for article (PubMed ID: 38700123)

  • 1. Solving Bongard Problems With a Visual Language and Pragmatic Constraints.
    Depeweg S; Rothkopf CA; Jäkel F
    Cogn Sci; 2024 May; 48(5):e13432. PubMed ID: 38700123
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Toward human-level concept learning: Pattern benchmarking for AI algorithms.
    Holzinger A; Saranti A; Angerschmid A; Finzel B; Schmid U; Mueller H
    Patterns (N Y); 2023 Aug; 4(8):100788. PubMed ID: 37602217
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Précis of bayesian rationality: The probabilistic approach to human reasoning.
    Oaksford M; Chater N
    Behav Brain Sci; 2009 Feb; 32(1):69-84; discussion 85-120. PubMed ID: 19210833
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Learning the compositional nature of visual object categories for recognition.
    Ommer B; Buhmann JM
    IEEE Trans Pattern Anal Mach Intell; 2010 Mar; 32(3):501-16. PubMed ID: 20075474
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A rational account of pedagogical reasoning: teaching by, and learning from, examples.
    Shafto P; Goodman ND; Griffiths TL
    Cogn Psychol; 2014 Jun; 71():55-89. PubMed ID: 24607849
    [TBL] [Abstract][Full Text] [Related]  

  • 6. AI, visual imagery, and a case study on the challenges posed by human intelligence tests.
    Kunda M
    Proc Natl Acad Sci U S A; 2020 Nov; 117(47):29390-29397. PubMed ID: 33229557
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Learning abstract visual concepts via probabilistic program induction in a Language of Thought.
    Overlan MC; Jacobs RA; Piantadosi ST
    Cognition; 2017 Nov; 168():320-334. PubMed ID: 28772189
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Engineering neural systems for high-level problem solving.
    Sylvester J; Reggia J
    Neural Netw; 2016 Jul; 79():37-52. PubMed ID: 27101230
    [TBL] [Abstract][Full Text] [Related]  

  • 9. How to grow a mind: statistics, structure, and abstraction.
    Tenenbaum JB; Kemp C; Griffiths TL; Goodman ND
    Science; 2011 Mar; 331(6022):1279-85. PubMed ID: 21393536
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Development and evaluation of RapTAT: a machine learning system for concept mapping of phrases from medical narratives.
    Gobbel GT; Reeves R; Jayaramaraja S; Giuse D; Speroff T; Brown SH; Elkin PL; Matheny ME
    J Biomed Inform; 2014 Apr; 48():54-65. PubMed ID: 24316051
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Perception and simulation during concept learning.
    Weitnauer E; Goldstone RL; Ritter H
    Psychol Rev; 2023 Oct; 130(5):1203-1238. PubMed ID: 37439723
    [TBL] [Abstract][Full Text] [Related]  

  • 12. The Boolean Language of Thought is recoverable from learning data.
    Carcassi F; Szymanik J
    Cognition; 2023 Oct; 239():105541. PubMed ID: 37473608
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Theory-based Bayesian models of inductive learning and reasoning.
    Tenenbaum JB; Griffiths TL; Kemp C
    Trends Cogn Sci; 2006 Jul; 10(7):309-18. PubMed ID: 16797219
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Divide et impera: subgoaling reduces the complexity of probabilistic inference and problem solving.
    Maisto D; Donnarumma F; Pezzulo G
    J R Soc Interface; 2015 Mar; 12(104):20141335. PubMed ID: 25652466
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Exemplar models as a mechanism for performing Bayesian inference.
    Shi L; Griffiths TL; Feldman NH; Sanborn AN
    Psychon Bull Rev; 2010 Aug; 17(4):443-64. PubMed ID: 20702863
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Compositional diversity in visual concept learning.
    Zhou Y; Feinman R; Lake BM
    Cognition; 2024 Mar; 244():105711. PubMed ID: 38224649
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A grounded theory of abstraction in artificial intelligence.
    Zucker JD
    Philos Trans R Soc Lond B Biol Sci; 2003 Jul; 358(1435):1293-309. PubMed ID: 12903672
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Constraint handling using tournament selection: abductive inference in partly deterministic bayesian networks.
    Galán SF; Mengshoel OJ
    Evol Comput; 2009; 17(1):55-88. PubMed ID: 19207088
    [TBL] [Abstract][Full Text] [Related]  

  • 19. The situated nature of concepts.
    Yeh W; Barsalou LW
    Am J Psychol; 2006; 119(3):349-84. PubMed ID: 17061691
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Incremental Bayesian Category Learning From Natural Language.
    Frermann L; Lapata M
    Cogn Sci; 2016 Aug; 40(6):1333-81. PubMed ID: 26534863
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.