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Exact Combinatorial Optimization with Graph Convolutional Neural Networks (NeurIPS 2019)
Hi, all, I want to ask that what the alternatives are for the function scip.Model.getState()? It seems that .getState() is an old-fashioned usage, and it is not available to see...
Hi, gasse! Recently,I am running your code on a MILP problem defined by myself. I find out the model: SVMRANK and GCNN do not work well on my problem.Do you...
Dear professor, Sorry for bothering. I got this error,  But I have install ecole via this,  Could you help me? How do...
Hello gasse, I have been read your paper very impressively. Currently, I am working on a task to solve the MILP problem of 100,000 by 100,000 sizes. Many attempts have...
Hi， I am running the codes on a combinatorial optimization problem defined by myself, which is similar to Capacitated Facility Location problem. However, the accuracy of the GCNN is low....
How to deal with the "Converting sparse IndexedSlices to a dense Tensor of unknown shape." problem
Hi, When I am running the codes in 03_train_gcnn.py there is a problem as following: **/root/miniconda3/envs/myenv/lib/python3.7/site-packages/tensorflow/python/ops/gradients_util.py:93: UserWarning: Converting sparse IndexedSlices to a dense Tensor of unknown shape. This may consume...
hi，I downloaded soplex-release-401.tar.gz and tried installing soplex. When I execute Cmake S- B build DCMAKE_ INSTALL_ PREFIX=$SCIPOPTDIR An error occurred /Home/cc/download/oplex-release-401/src/soplex/spxgitash. cpp: 17:10: fatal error: soplex/git_ Hash.cpp: There is no...
How to load the trained gcnn model to solve a specific MILP problem? I mean, where should I put my constraints and objective?
Hi & goog day! I've serached through the codes and paper a little bit and am wondering whether it's possible to work on a variant of VRP and recieve the...
Hello, Thanks for your great work. I am currently trying to reproduce it and stuck with some problems about tensorflow. I have successfully generated training dataset for setcover and meet...
