process-intelligence-research/ReLU_ANN_MILP
With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function. At the moment, only TensorFlow sequential models are supported. Interfaces to either the Pyomo or Gurobi modeling environments are offered.
PythonMIT
Stargazers
- ArturSchweidtmann@process-intelligence-research
- baibaify
- bertiqwerty@BASF
- bgrimstadSolution Seeker AS and Norwegian University of Science and Technology (NTNU)
- blackw1ngMunich, Germany
- DavidWalzBASF
- ddcerutiTU München
- DKenefakeTAMU Chemical Engineering
- donato-maragnoAmazon
- DrPride
- DrZhouKarlXiaomi
- ebigram
- gogolgrind
- gokhanceyhanJust Eat Takeaway.com
- Guo001northeastern University
- Gzy-best
- henryleeeee
- huan-roboticsHangzhou, China
- jdumouchelleUniversity of Toronto
- jS1ngle
- kookmaAmirkabir University of Technology
- lalala215Zhejiang Univeristy
- llueg
- lohsede
- maltefrankeCambridge, MA
- marcosfelt@Merck
- nairakhilsukuma
- qiminger
- rmisenerImperial College London
- RobertGoellingerRWTH Aachen University
- sanglinweiTsinghua University
- udovic2100
- Vbansal21None
- Wuhochi
- XinEDprob
- ZedTDeanGurobi