PhilSci Archive

Items where Subject is "Specific Sciences > Computer Science"

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Number of items at this level: 69.

A

Abbott, Russ (2015) Causality, computing, and complexity. UNSPECIFIED.

Abbott, Russ (2008) The reductionist blind spot. [Preprint]

Abbott, Russ (2009) The reductionist blind spot. [Preprint]

B

Baltag, Alexandru and Smets, Sonja (2004) The Logic of Quantum Programs. UNSPECIFIED. (In Press)

Barrett, Jeffrey A. and Skyrms, Brian and Cochran, Calvin (2018) Hierarchical Models for the Evolution of Compositional Language. [Preprint]

Beck, Micah (2016) On The Hourglass Model, The End-to-End Principle and Deployment Scalability. [Preprint]

Binder, Bernd (2002) Spacetime Memory: Phase-Locked Geometric Phases. [Preprint]

Bordg, Anthony (2019) Univalent Foundations and the UniMath Library. The Architecture of Mathematics. in Reflections on the Foundations of Mathematics, Synthese Library, 407.

Boyer-Kassem, Thomas and Imbert, Cyrille (2018) Explaining Scientific Collaboration: a General Functional Account. In: UNSPECIFIED.

Buckner, Cameron (2019) Deep Learning: A Philosophical Introduction. [Preprint]

C

Coelho Mollo, Dimitri (2019) Against Computational Perspectivalism. [Preprint]

Coelho Mollo, Dimitri (2019) Are There Teleological Functions to Compute? [Preprint]

Creel, Kathleen A. (2019) Transparency in Complex Computational Systems. [Preprint]

Cuffaro, Michael E. (2018) Universality, Invariance, and the Foundations of Computational Complexity in the light of the Quantum Computer. [Preprint]

Curtis-Trudel, Andre E (2020) Why do we need a theory of implementation? [Preprint]

D

De Florio, Vincenzo (2014) Behavior, Organization, Substance: Three Gestalts of General Systems Theory. Proc. of the 2014 Conference on Norbert Wiener in the 21st Century.

E

E. Szabó, László (2003) Formal Systems as Physical Objects: A Physicalist Account of Mathematical Truth. [Preprint]

Efstathiou, Sophia and Nydal, Rune and Laegreid, Astrid and Kuiper, Martin (2019) Scientific knowledge in the age of computation: Explicated, computable and manageable? THEORIA. An International Journal for Theory, History and Foundations of Science, 34 (2). pp. 213-236. ISSN 2171-679X

F

Floridi, Luciano (2008) Against Digital Ontology. [Preprint]

Floridi, Luciano (2008) Understanding Epistemic Relevance. [Preprint]

G

Greif, Hajo (2020) Invention, Intension and the Extension of the Computational Analogy. [Preprint]

H

Hagar, Amit and Korolev, Alex (2007) Quantum Hypercomputation - Hype or Computation? [Preprint]

Hewitt, Carl (2019) For Cybersecurity, Computer Science Must Rely on Strong Types. [Preprint]

Hewitt, Carl (2019) For Cybersecurity, Computer Science Must Rely on Strongly-Typed Actors. [Preprint]

Hewitt, Carl (2019) For Cybersecurity, Computer Science Must Rely on Strongly-Typed Actors. [Preprint]

Hewitt, Carl (2019) For Cybersecurity, Computer Science Must Rely on the Opposite of Gödel’s Results. [Preprint]

Hocquet, Alexandre and Wieber, Frederic (2017) “Only the Initiates Will Have the Secrets Revealed”: Computational Chemists and the Openness of Scientific Software. IEEE Annals of the History of Computing, 39 (4). pp. 40-58. ISSN 1058-6180

I

Imbert, Cyrille (2005) Why diachronically emergent properties must also be salient. [Preprint]

J

Johnson, Gabbrielle (2020) Algorithmic Bias: On the Implicit Biases of Social Technology. [Preprint]

K

Kim, Bryce (2017) Role of information and its processing in statistical analysis. [Preprint]

Kim, Bryce (2017) Role of information and its processing in statistical analysis. [Preprint]

Kim, Bryce (2016) What if we have only one universe and closed timelike curves exist? [Preprint]

Krzanowski, Roman (2017) Minimal Information Structural Realism. In: UNSPECIFIED.

L

Ladyman, James and Presnell, Stuart and Short, Anthony J. and Groisman, Berry (2006) The Connection between Logical and Thermodynamic Irreversibility. [Preprint]

Landgrebe, Jobst and Smith, Barry (2019) Making AI meaningful again. Synthese. ISSN 1573-0964

Luk, Robert (2010) Understanding scientific study via process modeling. Foundations of Science, 15 (1). pp. 49-78. ISSN 1233-1821

López-Rubio, Ezequiel (2020) The Big Data razor. [Preprint]

López-Rubio, Ezequiel and Ratti, Emanuele (2019) Data science and molecular biology: prediction and mechanistic explanation. [Preprint]

M

Maroney, O J E and Timpson, C G (2017) How is there a Physics of Information? On characterising physical evolution as information processing. [Preprint]

McCabe, Gordon (2004) Universe creation on a computer. [Preprint]

Miller, Ryan (2019) Nonrational Belief Paradoxes as Byzantine Failures. [Preprint]

Mitchell, Sandra D. (2019) Instrumental Perspectivism: Is AI Machine Learning Technology like NMR Spectroscopy? [Preprint]

N

Northcott, Robert (2019) Big data and prediction: four case studies. [Preprint]

P

Parker, Matthew W. (2006) Computing the Uncomputable, or, The Discrete Charm of Second-Order Simulacra. In: UNSPECIFIED. (Unpublished)

Parker, Matthew W. (2003) Undecidability in Rn: Riddled Basins, the KAM Tori, and the Stability of the Solar System. Philosophy of Science, 70 (2). pp. 359-382.

Parker, Matthew W. (2005) Undecidable Long-term Behavior in Classical Physics: Foundations, Results, and Interpretation.

Pence, Charles H. and Ramsey, Grant (2018) How to do digital philosophy of science. [Preprint]

Piccinini, Gualtiero (2004) Computers. UNSPECIFIED. (Unpublished)

Piccinini, Gualtiero (2004) The Functional Account of Computing Mechanisms. UNSPECIFIED. (Unpublished)

Pietsch, Wolfgang (2014) Aspects of theory-ladenness in data-intensive science. In: UNSPECIFIED.

Pietsch, Wolfgang (2013) Big Data – The New Science of Complexity. In: UNSPECIFIED.

Poldrack, Russell A. (2020) The physics of representation. [Preprint]

R

Ratti, Emanuele (2019) Phronesis and Automated Science: The Case of Machine Learning and Biology. [Preprint]

Ratti, Emanuele (2020) What Kind of Novelties Can Machine Learning Possibly Generate? The Case of Genomics. [Preprint]

S

Short, Tony and Ladyman, James and Groisman, Berry and Presnell, Stuart (2005) The Connection between Logical and Thermodynamical Irreversibility. [Preprint]

Sprenger, Jan (2017) Foundations of a Probabilistic Theory of Causal Strength. [Preprint]

Sterkenburg, Tom F. (2019) The Meta-Inductive Justification of Induction. Episteme.

Sterkenburg, Tom F. (2019) The Meta-Inductive Justification of Induction: The Pool of Strategies. Philosophy of Science.

Sterkenburg, Tom F. (2016) Solomonoff Prediction and Occam's Razor. Philosophy of Science, 83 (4). pp. 459-479.

Sterner, Beckett and Witteveen, Joeri and Franz, Nico (2019) Alternatives to Realist Consensus in Bio-Ontologies: Taxonomic Classification as a Basis for Data Discovery and Integration. [Preprint]

Sterrett, S. G. (2014) Turing on the Integration of Human and Machine Intelligence. [Preprint]

Stinson, Catherine (2019) From Implausible Artificial Neurons to Idealized Cognitive Models: Rebooting Philosophy of Artificial Intelligence. [Preprint]

Sullivan, Emily (2019) Understanding from Machine Learning Models. British Journal for the Philosophy of Science. ISSN 1464-3537

T

Tempini, N and Leonelli, Sabina (2018) Concealment and Discovery: The Role of Information Security in Biomedical Data Re-Use. [Preprint]

Tsementzis, Dimitris (2017) A Meaning Explanation for HoTT. [Preprint]

V

Vorobyev, Oleg Yu (2016) Postulating the theory of experience and chance as a theory of co~events (co~beings). [Preprint]

W

Wallace, Rodrick (2008) Lurching Toward Chernobyl: Dysfunctions of Real-Time Computation. [Preprint]

Wieber, Frederic and Hocquet, Alexandre (2018) Computational Chemistry as Voodoo Quantum Mechanics : Models, Parameterization, and Software. [Preprint]

Wronski, Leszek (2012) Branching Space-Times and Parallel Processing. H. Andersen et al. (eds.), New Challenges to Philosophy of Science, The Philosophy of Science in a European Perspective, 4. pp. 135-148.

This list was generated on Fri May 29 01:20:07 2020 EDT.