yassersouri / pytorch-deep-setsLinks
PyTorch re-implementation of parts of "Deep Sets" (NIPS 2017)
☆73Updated 7 years ago
Alternatives and similar repositories for pytorch-deep-sets
Users that are interested in pytorch-deep-sets are comparing it to the libraries listed below
Sorting:
- [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling☆41Updated 2 years ago
- [NeurIPS 2019] Deep Set Prediction Networks☆101Updated 5 years ago
- ☆77Updated 8 years ago
- Code for "Stochastic Optimization of Sorting Networks using Continuous Relaxations", ICLR 2019.☆150Updated 2 years ago
- a python implementation of various versions of the information bottleneck, including automated parameter searching☆132Updated 5 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆59Updated 4 years ago
- Code for "A Meta Transfer Objective For Learning To Disentangle Causal Mechanisms"☆127Updated 7 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆61Updated 6 years ago
- Mixed-curvature Variational Autoencoders (ICLR 2020)☆66Updated 5 years ago
- Hypergradient descent☆147Updated last year
- ☆44Updated 5 years ago
- Hyperbolic Hierarchical Clustering.☆207Updated 2 years ago
- code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".☆130Updated 2 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- LEARNING LATENT PERMUTATIONS WITH GUMBEL-SINKHORN NETWORKS IMPLEMENTATION WITH PYTORCH☆81Updated 2 years ago
- ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows☆54Updated 3 years ago
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆105Updated 6 years ago
- ☆126Updated last year
- implements optimal transport algorithms in pytorch☆104Updated 3 years ago
- Reproducing the paper "Variational Sparse Coding" for the ICLR 2019 Reproducibility Challenge☆62Updated 2 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆49Updated 8 years ago
- Official implementation of the paper "Topographic VAEs learn Equivariant Capsules"☆81Updated 3 years ago
- Reparameterize your PyTorch modules☆71Updated 5 years ago
- Codebase for Learning Invariances in Neural Networks☆96Updated 3 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆102Updated 7 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆112Updated 7 years ago
- Estimating Gradients for Discrete Random Variables by Sampling without Replacement☆40Updated 5 years ago
- Code for "Recurrent Independent Mechanisms"☆120Updated 3 years ago
- ☆54Updated last year