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PlantNSeek
PlantNSeek PublicRepository to the paper "Plant 'n' Seek: Can you find the winning ticket?" (ICLR 2022)
Python 5
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SpectralPruningBraess
SpectralPruningBraess PublicForked from AdarshMJ/SpectralPruningBraess
Codebase for "Spectral Graph Pruning Against Over-squashing and Over-smoothing" (NeurIPS 2024)
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LT-existence
LT-existence PublicIMCL 2022 paper "Convolutional and Residual Networks Provably Contain Lottery Tickets" and NeurIPS 2022 paper "Most Activation Functions Can Win the Lottery Without Excessive Depth"
Python 2
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sparse_to_sparse
sparse_to_sparse PublicICML 2023 paper "Why Random Pruning Is All We Need to Start Sparse"
Python 2
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UniversalLT
UniversalLT PublicCode accompanying the paper "On the Existence of Universal Lottery Tickets" (ICLR 2022)
Python 1
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Repositories
- relationalml.github.io Public
RelationalML/relationalml.github.io’s past year of commit activity - SpectralPruningBraess Public Forked from AdarshMJ/SpectralPruningBraess
Codebase for "Spectral Graph Pruning Against Over-squashing and Over-smoothing" (NeurIPS 2024)
RelationalML/SpectralPruningBraess’s past year of commit activity - Dynamic_Rescaling_GAT Public
Supplementary code for the paper 'Dynamic Rescaling for Training GNNs' to be published at NeurIPS 2024
RelationalML/Dynamic_Rescaling_GAT’s past year of commit activity - TurboPrune Public Forked from nelaturuharsha/TurboPrune
Harness for training/finding lottery tickets in PyTorch. With support for multiple pruning techniques and augmented by distributed training, FFCV and AMP.
RelationalML/TurboPrune’s past year of commit activity - GAT_Balanced_Initialization Public
Supplementary code for the paper 'Are GATs Out of Balance?' to be published at NeurIPS 2023
RelationalML/GAT_Balanced_Initialization’s past year of commit activity - BaselineGNNs Public
RelationalML/BaselineGNNs’s past year of commit activity - LT-existence Public
IMCL 2022 paper "Convolutional and Residual Networks Provably Contain Lottery Tickets" and NeurIPS 2022 paper "Most Activation Functions Can Win the Lottery Without Excessive Depth"
RelationalML/LT-existence’s past year of commit activity