authors-1901-10912 / A-Meta-Transfer-Objective-For-Learning-To-Disentangle-Causal-MechanismsLinks
Code for "A Meta Transfer Objective For Learning To Disentangle Causal Mechanisms"
☆127Updated 7 years ago
Alternatives and similar repositories for A-Meta-Transfer-Objective-For-Learning-To-Disentangle-Causal-Mechanisms
Users that are interested in A-Meta-Transfer-Objective-For-Learning-To-Disentangle-Causal-Mechanisms are comparing it to the libraries listed below
Sorting:
- Code for "Recurrent Independent Mechanisms"☆120Updated 3 years ago
- Code for "Neural causal learning from unknown interventions"☆104Updated 5 years ago
- a python implementation of various versions of the information bottleneck, including automated parameter searching☆132Updated 5 years ago
- ☆65Updated last year
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 3 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆102Updated 7 years ago
- Implementation of the paper Recurrent Independent Mechanisms (https://arxiv.org/pdf/1909.10893.pdf)☆101Updated 4 years ago
- Code to reproduce experiments in "Meta-learning probabilistic inference for prediction"☆69Updated 4 years ago
- ☆63Updated 5 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆42Updated 3 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆43Updated 4 years ago
- Measuring compositionality in representation learning☆73Updated 6 years ago
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆91Updated 5 years ago
- PyTorch Implementation of Neural Statistician☆61Updated 3 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- ☆78Updated 4 years ago
- Computing various norms/measures on over-parametrized neural networks☆50Updated 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
- Implementation of the paper "Direct Optimization through argmax for discrete Variational Auto-Encoder"☆15Updated 5 years ago
- Implementation of the variational continual learning method☆195Updated 6 years ago
- This repository contains implementations of the paper, Bayesian Model-Agnostic Meta-Learning.☆61Updated 6 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 3 years ago
- Memory efficient MAML using gradient checkpointing☆86Updated 6 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated last year
- Hypergradient descent☆147Updated last year
- ☆69Updated 5 years ago
- Code for the "Neural Expectation Maximization" paper.☆126Updated 3 years ago
- ☆79Updated 9 months ago
- An implementation of DIP-VAE from the paper "Variational Inference of Disentangled Latent Concepts from Unlabelled Observations" by Kumar…☆26Updated 7 years ago
- pytorch implementation of VAE-Gumble-Softmax☆63Updated 5 years ago