NNReasoning / What-Can-Neural-Networks-Reason-AboutLinks
☆44Updated 5 years ago
Alternatives and similar repositories for What-Can-Neural-Networks-Reason-About
Users that are interested in What-Can-Neural-Networks-Reason-About are comparing it to the libraries listed below
Sorting:
- [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling☆41Updated 2 years ago
- Code for Reparameterizable Subset Sampling via Continuous Relaxations, IJCAI 2019.☆57Updated 2 years ago
- Mixed-curvature Variational Autoencoders (ICLR 2020)☆66Updated 5 years ago
- ☆65Updated last year
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆105Updated 6 years ago
- Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs☆34Updated 5 years ago
- Low-variance and unbiased gradient for backpropagation through categorical random variables, with application in variational auto-encoder…☆17Updated 5 years ago
- Hyperbolic Neural Networks, pytorch☆87Updated 6 years ago
- Code for Graph Neural Networks Exponentially Lose Expressive Power for Node Classification.☆30Updated 5 years ago
- D-VAE: A Variational Autoencoder for Directed Acyclic Graphs, NeurIPS 2019☆145Updated 5 years ago
- ☆69Updated 5 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆37Updated 5 years ago
- ☆54Updated 3 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆59Updated 4 years ago
- ☆15Updated 5 years ago
- SetToGraph paper repository☆22Updated 5 years ago
- [ICML'21] Improved Contrastive Divergence Training of Energy Based Models☆69Updated 3 years ago
- G2SAT: Learning to Generate SAT Formulas☆50Updated 5 years ago
- ☆77Updated 8 years ago
- implements optimal transport algorithms in pytorch☆104Updated 3 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- Equivalence Between Structural Representations and Positional Node Embeddings☆22Updated 5 years ago
- Code for "Stochastic Optimization of Sorting Networks using Continuous Relaxations", ICLR 2019.☆150Updated 2 years ago
- Implicit Graph Neural Networks☆64Updated 4 years ago
- Memory-Based Graph Networks☆104Updated 3 years ago
- ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows☆54Updated 3 years ago
- Code for "Neural causal learning from unknown interventions"☆104Updated 5 years ago
- code for paper "Graph Structure of Neural Networks"☆156Updated 4 years ago
- PyTorch re-implementation of parts of "Deep Sets" (NIPS 2017)☆73Updated 7 years ago
- Reparameterize your PyTorch modules☆71Updated 5 years ago