Valentin Mayer-Eichberger
Valentin Mayer-Eichberger
Technische Universität Berlin
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TitleCited byYear
A new look at bdds for pseudo-boolean constraints
I Abío, R Nieuwenhuis, A Oliveras, E Rodríguez-Carbonell, ...
Journal of Artificial Intelligence Research 45, 443-480, 2012
On CNF encodings of decision diagrams
I Abío, G Gange, V Mayer-Eichberger, PJ Stuckey
International Conference on AI and OR Techniques in Constraint Programming …, 2016
Encoding linear constraints with implication chains to CNF
I Abío, V Mayer-Eichberger, PJ Stuckey
International Conference on Principles and Practice of Constraint …, 2015
SAT and hybrid models of the car sequencing problem
C Artigues, E Hebrard, V Mayer-Eichberger, M Siala, T Walsh
International Conference on AI and OR Techniques in Constriant Programming …, 2014
Extracting Propositional Rules from Feed-forward Neural Networks-A New Decompositional Approach.
S Bader, S Hölldobler, V Mayer-Eichberger
NeSy, 2007
Towards solving a system of pseudo boolean constraints with binary decision diagrams
V Mayer-Eichberger
Master's thesis, Lisbon, 2008
There’s more than one way to solve a long-haul transportation problem
P Kilby, I Abio, D Guimarans, D Harabor, P Haslum, V Mayer-Eichberger, ...
Vehicle Routing and Logistics (VeRoLog).(Abstract.), 2015
SAT Encodings for the Car Sequencing Problem.
V Mayer-Eichberger, T Walsh
POS@ SAT, 15-27, 2013
Modelling Satisfiability Problems: Theory and Practice.
V Mayer-Eichberger
IJCAI, 4012-4013, 2016
Just-in-time hierarchical constraint decomposition
V Mayer-Eichberger
Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
SAT Benchmark for the Car Sequencing Problem
V Mayer-Eichberger
SAT COMPETITION 2013, 114, 2013
Extracting Propositional Logic Programs From Neural Networks: A Decompositional Approach
V Mayer-Eichberger, MSS Bader
CP Doctoral Program 2013
A Balafrej, S Brockbank, C Cornelio, C Dejemeppe, E Delisle, A Derrien, ...
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Articles 1–13