Alternatives and similar repositories for ame:

Users that are interested in ame are comparing it to the libraries listed below

• kakaobrain / irm-empirical-study
  An Empirical Study of Invariant Risk Minimization
  ☆27Updated 4 years ago
• blei-lab / ars-reparameterization
  Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)
  ☆39Updated 7 years ago
• ec6dde01667145e58de60f864e05a4 / CausalOptimizationAnon
  ☆65Updated 6 months ago
• nke001 / causal_learning_unknown_interventions
  Code for "Neural causal learning from unknown interventions"
  ☆100Updated 4 years ago
• KyleGoyette / nnRNN
  ☆24Updated 5 years ago
• anirbanl / sparsegen
  Code for the NeurIPS 2018 paper "On Controllable Sparse Alternatives to Softmax"
  ☆22Updated 5 years ago
• siplab-gt / generative-causal-explanations
  Code for "Generative causal explanations of black-box classifiers"
  ☆33Updated 4 years ago
• kingofspace0wzz / wae-rnf-lm
  Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…
  ☆62Updated 4 years ago
• giannisnik / repset
  Rep the Set: Neural Networks for Learning Set Representations
  ☆29Updated 4 years ago
• sidak / context-mover-distance-and-barycenters
  Code accompanying our paper at AISTATS 2020
  ☆21Updated 4 years ago
• dtak / ocbnn-public
  General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
  ☆38Updated 2 years ago
• is0383kk / Dirichlet-VAE
  Dirichlet-Variational Auto-Encoder by PyTorch
  ☆22Updated last year
• facebookresearch / Permutation-Equivariant-Seq2Seq
  Humans understand novel sentences by composing meanings and roles of core language components. In contrast, neural network models for nat…
  ☆27Updated 4 years ago
• microsoft / EDDI
  Code for paper EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE
  ☆37Updated last year
• msobroza / SparsemaxPytorch
  SparseMax activation function implementation (ICML 2016) (PyTorch)
  ☆27Updated 7 years ago
• prasoongoyal / bnp-vae
  ☆11Updated 6 years ago
• lethaiq / GRACE_KDD20
  GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model’s Prediction. Thai Le, Suhang Wang, Dongwon …
  ☆21Updated 4 years ago
• bobchennan / VAE_NBP
  Variational Auto-encoder with Non-parametric Bayesian Prior
  ☆42Updated 7 years ago
• enalisnick / mixture_density_VAEs
  Variational Autoencoders with Gaussian Mixture Latent Space
  ☆36Updated 7 years ago
• mducoffe / Learning-Wasserstein-Embeddings
  Keras implementation of Deep Wasserstein Embeddings
  ☆47Updated 6 years ago
• franrruiz / vcd_divergence
  Code to minimize the Variational Contrastive Divergence (VCD)
  ☆28Updated 5 years ago
• OATML / ucate
  Uncertainty in Conditional Average Treatment Effect Estimation
  ☆29Updated 3 years ago
• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• paruby / DIP-VAE
  An implementation of DIP-VAE from the paper "Variational Inference of Disentangled Latent Concepts from Unlabelled Observations" by Kumar…
  ☆24Updated 6 years ago
• Cyanogenoid / fspool
  [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling
  ☆42Updated last year
• code-terminator / invariant_rationalization
  Tensorflow implementation of Invariant Rationalization
  ☆49Updated 2 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 6 years ago
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆130Updated 4 years ago
• TropComplique / set-transformer
  A neural network architecture for prediction on sets
  ☆22Updated 2 years ago
• anndvision / quince
  Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
  ☆21Updated 2 years ago