TropComplique / set-transformerLinks
A neural network architecture for prediction on sets
☆22Updated 3 years ago
Alternatives and similar repositories for set-transformer
Users that are interested in set-transformer are comparing it to the libraries listed below
Sorting:
- ☆65Updated last year
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 3 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 2 years ago
- ☆63Updated 4 years ago
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆90Updated 5 years ago
- Implementation of the paper "Direct Optimization through argmax for discrete Variational Auto-Encoder"☆14Updated 4 years ago
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 3 years ago
- ☆76Updated 7 years ago
- [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling☆42Updated last year
- code for the ICML paper "SelectiveNet - A Deep Neural Network with an Integrated Reject Option"☆46Updated 6 years ago
- PyTorch Implementation of Neural Statistician☆60Updated 3 years ago
- Code for "Recurrent Independent Mechanisms"☆118Updated 3 years ago
- Code for "A Meta Transfer Objective For Learning To Disentangle Causal Mechanisms"☆127Updated 6 years ago
- PyTorch re-implementation of parts of "Deep Sets" (NIPS 2017)☆72Updated 7 years ago
- implements optimal transport algorithms in pytorch☆100Updated 3 years ago
- An Empirical Study of Invariant Risk Minimization☆27Updated 5 years ago
- Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…☆63Updated 5 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- PyTorch Implementations of Dropout Variants☆87Updated 7 years ago
- ☆44Updated 5 years ago
- Code for "Neural causal learning from unknown interventions"☆104Updated 5 years ago
- Code to implement the AND-mask and geometric mean to do gradient based optimization, from the paper "Learning explanations that are hard …☆40Updated 4 years ago
- Code for Reparameterizable Subset Sampling via Continuous Relaxations, IJCAI 2019.☆57Updated last year
- Reparameterize your PyTorch modules☆71Updated 4 years ago
- A Pytorch implementation of the optimal transport kernel embedding☆117Updated 4 years ago
- Code to reproduce experiments in "Meta-learning probabilistic inference for prediction"☆69Updated 4 years ago
- Hybrid Discriminative-Generative Training via Contrastive Learning☆75Updated 2 years ago
- code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".☆127Updated last year
- Implementation of the paper "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory", Ron Amit and Ron Meir, ICML 2018☆22Updated 5 years ago
- a python implementation of various versions of the information bottleneck, including automated parameter searching☆128Updated 5 years ago