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Theoretical Foundation of Solvers: Context, Directions and Open Problems

Vijay Ganesh (University of Waterloo), Laurent Simon (Bordeaux INP), and David …
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Theoretical Foundation of Solvers: Context, Directions and Open Problems

Vijay Ganesh (University of Waterloo), Laurent Simon (Bordeaux INP), and David …
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Theoretical Foundation of Solvers: Context, Directions and Open Problems

Vijay Ganesh (University of Waterloo), Laurent Simon (Bordeaux INP), and David …
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Structure of SAT Instances

Jordi Levy (Artificial Intelligence Research Institute, Spanish National Resear…
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Structure of SAT Instances

Jordi Levy (Artificial Intelligence Research Institute, Spanish National Resear…
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Structure of SAT Instances

Jordi Levy (Artificial Intelligence Research Institute, Spanish National Resear…
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Theory of Encodings

Oliver Kullmann (Swansea University), Ciaran McCreesh (University of Glasgow), …
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Theory of Encodings

Oliver Kullmann (Swansea University), Ciaran McCreesh (University of Glasgow), …
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Theory of Encodings

Oliver Kullmann (Swansea University), Ciaran McCreesh (University of Glasgow), …
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Proof Complexity Toolbox

Robert Robere (McGill University), Susanna de Rezende (Czech Academy of Science…
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Proof Complexity Toolbox

Robert Robere (McGill University), Susanna de Rezende (Czech Academy of Science…
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Proof Complexity Toolbox

Robert Robere (McGill University), Susanna de Rezende (Czech Academy of Science…
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ML for Solvers
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Predicting Satisfiability at the Phase Transition via End-to-End Learning

Kevin Leyton Brown (University of British Columbia)
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Learning to Schedule Heuristics in Branch and Bound

Elias Khalil (University of Toronto)
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Learning to Solve SMT Formulas

Mislav Balunović (ETH Zurich)
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Preprocessing SAT, MaxSAT, and QBF

Benjamin Kiesl (SAP), Jeremias Berg (University of Helsinki), and Martina Seidl…
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Preprocessing SAT, MaxSAT, and QBF

Benjamin Kiesl (SAP), Jeremias Berg (University of Helsinki), and Martina Seidl…
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Preprocessing SAT, MaxSAT, and QBF

Benjamin Kiesl (SAP), Jeremias Berg (University of Helsinki), and Martina Seidl…
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Logic + Machine Learning
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Unifying Logical and Statistical AI with Markov Logic

Pedro Domingos (University of Washington)
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Constrained Gradient Descent Algorithm for Testing Neural Networks

Vineel Nagisetty (University of Waterloo)
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