Added all experiments for Graph Extended Filtration Learning, readout…

… ablation study, filtration convolution length experiment, and the standard GNN baseline.

2cycles_average.sh

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+#!/bin/bash
+
+for iter in {0..0}
+  do
+  dataset="2cycles"
+  name=${dataset}-${iter}
+  python3 -m train.2cycles_train_eval --readout average --num_epochs 100 --batch_size 128 --output_dir ./results --device 0 --exp_name ${name} #&> imdb-multi-slurmfiles/slurm-${SLURM_JOB_ID}.out
+  done

2cycles_extpers.sh

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+#!/bin/bash
+
+for iter in {0..0}
+  do
+  dataset="2cycles"
+  name=${dataset}-${iter}
+  python3 -m train.2cycles_train_eval --readout extph --num_epochs 100 --batch_size 128 --output_dir ./results --device 0 --exp_name ${name} #&> imdb-multi-slurmfiles/slurm-${SLURM_JOB_ID}.out
+  done

2cycles_max.sh

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+#!/bin/bash
+
+for iter in {0..0}
+  do
+  dataset="2cycles"
+  name=${dataset}-${iter}
+  python3 -m train.2cycles_train_eval --readout max --num_epochs 100 --batch_size 128 --output_dir ./results --device 0 --exp_name ${name} #&> imdb-multi-slurmfiles/slurm-${SLURM_JOB_ID}.out
+  done

2cycles_sum.sh

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+#!/bin/bash
+
+for iter in {0..0}
+  do
+  dataset="2cycles"
+  name=${dataset}-${iter}
+  python3 -m train.2cycles_train_eval --readout sum --num_epochs 100 --batch_size 128 --output_dir ./results --device 0 --exp_name ${name} #&> imdb-multi-slurmfiles/slurm-${SLURM_JOB_ID}.out
+  done

README.md

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+#Graph Extended Filtration Learning
+
+## Summary
+It is impossible for a standard message passing GNN with finite receptive field to distinguish arbitrary cycle lengths for graph classification. We address this problem by using extended persistence in the readout function. Extended persistence is a quantifiable multiscale method to capture the relative prominence of cycles and connected components. We also improve the computation of extended perisistence by using a link-cut tree data structure to dynamically maintain cycle information and introduce parallelism. 
+
+## Installation
+* python==3.9.1
+* torch==1.10.1
+* CUDA==11.2
+* GCC==7.5.0
+* torch-geometric==2.0.5
+* torch-scatter==2.0.9
+* torch-sparse==0.6.13
+
+## Running Experiments
+Replace "proteins" with any of dd/mutag/imdb-multi/molbace/molbbbp/2cycles/pinwheels below to run experiment on any dataset
+
+To run the proteins readout ablation experiment run the following commands (in parallel):
+
+```
+source proteins_extpers.sh
+
+source proteins_sum.sh
+
+source proteins_max.sh
+
+source proteins_average.sh
+```
+
+In general, change the --readout flag to the readout function of choice in the shell file.
+
+To run the proteins filtration convolution length experiment, run the following commands (in parallel):
+```
+source proteinslen1_sup.sh
+
+source proteinslen2_sup.sh
+
+source proteinslen3_sup.sh
+
+source proteinslen4_sup.sh
+
+source proteinslen5_sup.sh
+```
+
+To run the standard message passing graph neural network baseline, run the command:
+
+```
+cd external_experiments/sup_baseline
+
+source run_sup_baseline.sh
+```
+