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#satisfiability — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #satisfiability, aggregated by home.social.

  1. Plongez dans la logique du premier ordre avec IFT6755 ! Une présentation claire et pédagogique de satisfiability et validity en FOL — parfait pour étudiant·e·s et curieux·ses. Exemples concrets et intuition pour maîtriser ces concepts essentiels. #FOL #Logique #Satisfiability #Validity #Informatique #Education #French #IFT6755
    classe.iro.umontreal.ca/videos

  2. #NeuralNetworks and the #Satisfiability Problem” is the 2019 Stanford PhD dissertation by Salsam. It describes NeuroSAT, a #GNN, that learns to solve propositional satisfiability #SAT, that simple, yet quintessentially NP-complete, problem.

    Salsam is an active member of the #Lean theorem prover community, who had worked closely with de Moura.

    stacks.stanford.edu/file/druid

  3. #NeuralNetworks and the #Satisfiability Problem” is the 2019 Stanford PhD dissertation by Salsam. It describes NeuroSAT, a #GNN, that learns to solve propositional satisfiability #SAT, that simple, yet quintessentially NP-complete, problem.

    Salsam is an active member of the #Lean theorem prover community, who had worked closely with de Moura.

    stacks.stanford.edu/file/druid

  4. #NeuralNetworks and the #Satisfiability Problem” is the 2019 Stanford PhD dissertation by Salsam. It describes NeuroSAT, a #GNN, that learns to solve propositional satisfiability #SAT, that simple, yet quintessentially NP-complete, problem.

    Salsam is an active member of the #Lean theorem prover community, who had worked closely with de Moura.

    stacks.stanford.edu/file/druid

  5. #NeuralNetworks and the #Satisfiability Problem” is the 2019 Stanford PhD dissertation by Salsam. It describes NeuroSAT, a #GNN, that learns to solve propositional satisfiability #SAT, that simple, yet quintessentially NP-complete, problem.

    Salsam is an active member of the #Lean theorem prover community, who had worked closely with de Moura.

    stacks.stanford.edu/file/druid

  6. #NeuralNetworks and the #Satisfiability Problem” is the 2019 Stanford PhD dissertation by Salsam. It describes NeuroSAT, a #GNN, that learns to solve propositional satisfiability #SAT, that simple, yet quintessentially NP-complete, problem.

    Salsam is an active member of the #Lean theorem prover community, who had worked closely with de Moura.

    stacks.stanford.edu/file/druid

  7. 'Critically Assessing the State of the Art in Neural Network Verification', by Matthias König, Annelot W. Bosman, Holger H. Hoos, Jan N. van Rijn.

    jmlr.org/papers/v25/23-0119.ht

    #robustness #benchmarks #satisfiability

  8. 'Critically Assessing the State of the Art in Neural Network Verification', by Matthias König, Annelot W. Bosman, Holger H. Hoos, Jan N. van Rijn.

    jmlr.org/papers/v25/23-0119.ht

    #robustness #benchmarks #satisfiability

  9. 'Critically Assessing the State of the Art in Neural Network Verification', by Matthias König, Annelot W. Bosman, Holger H. Hoos, Jan N. van Rijn.

    jmlr.org/papers/v25/23-0119.ht

    #robustness #benchmarks #satisfiability

  10. 'Critically Assessing the State of the Art in Neural Network Verification', by Matthias König, Annelot W. Bosman, Holger H. Hoos, Jan N. van Rijn.

    jmlr.org/papers/v25/23-0119.ht

    #robustness #benchmarks #satisfiability

  11. 'Critically Assessing the State of the Art in Neural Network Verification', by Matthias König, Annelot W. Bosman, Holger H. Hoos, Jan N. van Rijn.

    jmlr.org/papers/v25/23-0119.ht

    #robustness #benchmarks #satisfiability

  12. Weekend project: try to solve some #combinatorics #enumeration problems by reduction to #SharpSAT. (Which, to be clear, I thought was unlikely to succeed!)

    I picked c2d reasoning.cs.ucla.edu/c2d/ because it scored highly in the 2020 Model Counting Competition arxiv.org/abs/2012.01323 but I am not sure this is the same version. The one I got is dated 2005 and was 32-bit only. It ran out of memory on this 364-variable 942-clause instance (corresponding to 6 playing cards chosen from a standard 52-card deck.)

    Looking at the 2023 competition instead, I think I should try SharpSAT-TD github.com/Laakeri/sharpsat-td but it is not as well documented. For example, I don't know if it supports the "eclauses" (exactly-one clauses) extension of the Dimacs CNF format.

    #Satisfiability

  13. Weekend project: try to solve some #combinatorics #enumeration problems by reduction to #SharpSAT. (Which, to be clear, I thought was unlikely to succeed!)

    I picked c2d reasoning.cs.ucla.edu/c2d/ because it scored highly in the 2020 Model Counting Competition arxiv.org/abs/2012.01323 but I am not sure this is the same version. The one I got is dated 2005 and was 32-bit only. It ran out of memory on this 364-variable 942-clause instance (corresponding to 6 playing cards chosen from a standard 52-card deck.)

    Looking at the 2023 competition instead, I think I should try SharpSAT-TD github.com/Laakeri/sharpsat-td but it is not as well documented. For example, I don't know if it supports the "eclauses" (exactly-one clauses) extension of the Dimacs CNF format.

    #Satisfiability

  14. Weekend project: try to solve some #combinatorics #enumeration problems by reduction to #SharpSAT. (Which, to be clear, I thought was unlikely to succeed!)

    I picked c2d reasoning.cs.ucla.edu/c2d/ because it scored highly in the 2020 Model Counting Competition arxiv.org/abs/2012.01323 but I am not sure this is the same version. The one I got is dated 2005 and was 32-bit only. It ran out of memory on this 364-variable 942-clause instance (corresponding to 6 playing cards chosen from a standard 52-card deck.)

    Looking at the 2023 competition instead, I think I should try SharpSAT-TD github.com/Laakeri/sharpsat-td but it is not as well documented. For example, I don't know if it supports the "eclauses" (exactly-one clauses) extension of the Dimacs CNF format.

    #Satisfiability

  15. Weekend project: try to solve some #combinatorics #enumeration problems by reduction to #SharpSAT. (Which, to be clear, I thought was unlikely to succeed!)

    I picked c2d reasoning.cs.ucla.edu/c2d/ because it scored highly in the 2020 Model Counting Competition arxiv.org/abs/2012.01323 but I am not sure this is the same version. The one I got is dated 2005 and was 32-bit only. It ran out of memory on this 364-variable 942-clause instance (corresponding to 6 playing cards chosen from a standard 52-card deck.)

    Looking at the 2023 competition instead, I think I should try SharpSAT-TD github.com/Laakeri/sharpsat-td but it is not as well documented. For example, I don't know if it supports the "eclauses" (exactly-one clauses) extension of the Dimacs CNF format.

    #Satisfiability

  16. Papers that were sadly not accepted to SAT 2023, can be revised and submitted to CP 2023 in a special fast track:

    - SAT fast track abstract registration: May 1, 2023
    - SAT fast track paper submission: May 17, 2023

    #Satisfiability #AI #CP2023 #CfP #ConstraintProgramming #AcademicMastodon #CFP #CallForPapers

  17. Papers that were sadly not accepted to SAT 2023, can be revised and submitted to CP 2023 in a special fast track:

    - SAT fast track abstract registration: May 1, 2023
    - SAT fast track paper submission: May 17, 2023

    #Satisfiability #AI #CP2023 #CfP #ConstraintProgramming #AcademicMastodon #CFP #CallForPapers

  18. Papers that were sadly not accepted to SAT 2023, can be revised and submitted to CP 2023 in a special fast track:

    - SAT fast track abstract registration: May 1, 2023
    - SAT fast track paper submission: May 17, 2023

    #Satisfiability #AI #CP2023 #CfP #ConstraintProgramming #AcademicMastodon #CFP #CallForPapers

  19. Papers that were sadly not accepted to SAT 2023, can be revised and submitted to CP 2023 in a special fast track:

    - SAT fast track abstract registration: May 1, 2023
    - SAT fast track paper submission: May 17, 2023

    #Satisfiability #AI #CP2023 #CfP #ConstraintProgramming #AcademicMastodon #CFP #CallForPapers