Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
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Updated
Jun 11, 2020 - Python
Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
Github code for the paper Maximum Class Separation as Inductive Bias in One Matrix. Arxiv link: https://arxiv.org/abs/2206.08704
Code for "Learning Inductive Biases with Simple Neural Networks" (Feinman & Lake, 2018).
Emergent Communication Pretraining for Few-Shot Machine Translation
Implementation code of GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference accepted by Medical Image Computing and Computer Assisted Interventions (MICCAI 2021)
This is the official code for CoLLAs 2022 paper, "InBiaseD: Inductive Bias Distillation to Improve Generalization and Robustness through Shape-awareness"
Utility repository for the processing and visualizing NADs of arbitrary PyTorch models
Towards Exact Computation of Inductive Bias (IJCAI 2024)
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