PhilSci Archive

Items where Subject is "Specific Sciences > Computer Science"

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Number of items at this level: 89.

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]

Abrams, Marshall (2021) Pseudorandomness in Simulations and Nature. In: UNSPECIFIED.

B

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

Barrett, Jeffrey A. and Gabriel, Nathan (2021) Reinforcement with Iterative Punishment. [Preprint]

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]

Belot, Gordon (2020) Absolutely No Free Lunches! [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.

Bruineberg, Jelle and Dolega, Krzysztof and Dewhurst, Joe and Baltieri, Manuel (2020) The Emperor’s New Markov Blankets. [Preprint]

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) Implementation as Resemblance. In: UNSPECIFIED.

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

Eva, Benjamin and Shear, Ted and Fitelson, Branden (2020) Four Approaches to Supposition. [Preprint]

F

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

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

G

Greif, Hajo (2020) Invention, Intension and the Limits of Computation. [Preprint]

Grimsley, Christopher (2020) Causal and Non-Causal Explanations of Artificial Intelligence. In: UNSPECIFIED.

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 (2021) Epistemic issues in computational reproducibility: software as the elephant in the room. European Journal for Philosophy of Science. ISSN 1879-4912

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

Jebeile, Julie and Lam, Vincent and Räz, Tim (2020) Understanding Climate Change with Statistical Downscaling and Machine Learning. [Preprint]

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

K

Kasirzadeh, Atoosa and Klein, Colin (2021) The Ethical Gravity Thesis: Marrian Levels and the Persistence of Bias in Automated Decision-making Systems. Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society.

Ketland, Jeffrey (2020) Computation and Indispensability. Logic and Logical Philosophy, 30.

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

Papayannopoulos, Philippos (2020) Unrealistic Models for Realistic Computations: How Idealisations Help Represent Mathematical Structures and Found Scientific Computing. [Preprint]

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.

Plutniak, Sébastien (2021) Assyrian merchants meet nuclear physicists: history of the early contributions from social sciences to computer science. The case of automatic pattern detection in graphs (1950s-1970s). Interdisciplinary Science Reviews, 46 (4). pp. 547-568. ISSN 0308-0188

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

R

Ramstead, Maxwell J. D. and Wiese, Wanja and Miller, Mark and Friston, Karl J. (2020) Deep neurophenomenology: An active inference account of some features of conscious experience and of their disturbance in major depressive disorder. [Preprint]

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]

Rosenstock, Sarita (2020) Learning from the Shape of Data. In: UNSPECIFIED.

Räz, Tim (2020) Understanding Deep Learning With Statistical Relevance. [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.

Sterkenburg, Tom F. and Grünwald, Peter D. (2020) The No-Free-Lunch Theorems of Supervised Learning. [Preprint]

Sterkenburg, Tom F. and Grünwald, Peter D. (2021) The No-Free-Lunch Theorems of Supervised Learning. Synthese.

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

Tabatabaei Ghomi, Hamed (2021) Setting the demons loose: computational irreducibility does not guarantee unpredictability or emergence. [Preprint]

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]

Wieber, Frederic and Hocquet, Alexandre (2020) Models, parameterization, and software: epistemic opacity in computational chemistry. Perspectives on Science, 28 (5). pp. 610-629. ISSN 1063-6145

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 Wed Dec 1 13:06:32 2021 EST.