ermongroup / subsets
Code for Reparameterizable Subset Sampling via Continuous Relaxations, IJCAI 2019.
☆55Updated last year
Alternatives and similar repositories for subsets:
Users that are interested in subsets are comparing it to the libraries listed below
- ☆65Updated 9 months ago
- Low-variance and unbiased gradient for backpropagation through categorical random variables, with application in variational auto-encoder…☆17Updated 4 years ago
- ☆45Updated 4 years ago
- [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling☆42Updated last year
- Generator loss to reduce mode-collapse and to improve the generated samples quality.☆34Updated 5 years ago
- A supplementary code for Editable Neural Networks, an ICLR 2020 submission.☆46Updated 5 years ago
- Learning To Stop While Learning To Predict☆34Updated 2 years ago
- A Pytorch implementation of the optimal transport kernel embedding☆116Updated 4 years ago
- Hyperbolic Neural Networks, pytorch☆86Updated 5 years ago
- Gradients as Features for Deep Representation Learning☆43Updated 5 years ago
- implements optimal transport algorithms in pytorch☆96Updated 2 years ago
- NeurIPS 2021, Code for Measuring Generalization with Optimal Transport☆28Updated 3 years ago
- Weighted Training for Cross-Task Learning☆15Updated 2 years ago
- An adaptive training algorithm for residual network☆15Updated 4 years ago
- Implementation of the paper "Direct Optimization through argmax for discrete Variational Auto-Encoder"☆14Updated 4 years ago
- Code for the NeurIPS 2018 paper "On Controllable Sparse Alternatives to Softmax"☆23Updated 5 years ago
- Tensorflow implementation of Invariant Rationalization☆49Updated 2 years ago
- LEARNING LATENT PERMUTATIONS WITH GUMBEL-SINKHORN NETWORKS IMPLEMENTATION WITH PYTORCH☆79Updated last year
- ☆14Updated 5 years ago
- Reparameterize your PyTorch modules☆71Updated 4 years ago
- ☆34Updated 4 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 6 years ago
- ☆64Updated 4 years ago
- Estimating Gradients for Discrete Random Variables by Sampling without Replacement☆40Updated 5 years ago
- Tensorflow implementation of "Meta Dropout: Learning to Perturb Latent Features for Generalization" (ICLR 2020)☆27Updated 4 years ago
- Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs☆34Updated 5 years ago
- ☆30Updated 3 years ago
- pytorch implementation of VAE-Gumble-Softmax☆62Updated 4 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆55Updated 3 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 2 years ago