davidinouye / destructive-deep-learning
Destructive deep learning estimators and functions that are compatible with scikit-learn.
☆19Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for destructive-deep-learning
- Computing various norms/measures on over-parametrized neural networks☆49Updated 5 years ago
- Implementation of iterative inference in deep latent variable models☆43Updated 5 years ago
- Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019☆39Updated 4 years ago
- Starter Kit for the NeurIPS 2019 Disentanglement Challenge☆33Updated 2 years ago
- Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018☆39Updated 5 years ago
- ☆26Updated 5 years ago
- [NeurIPS'19] [PyTorch] Adaptive Regularization in NN☆67Updated 5 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 4 years ago
- Implementation of REBAR in PyTorch☆17Updated 6 years ago
- An implementation of DIP-VAE from the paper "Variational Inference of Disentangled Latent Concepts from Unlabelled Observations" by Kumar…☆24Updated 6 years ago
- Code for Stochastic Hyperparameter Optimization through Hypernetworks☆23Updated 6 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆50Updated 7 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 5 years ago
- Geometric Certifications of Neural Nets☆41Updated 2 years ago
- Scaled MMD GAN☆36Updated 5 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆32Updated last year
- The Variational Homoencoder: Learning to learn high capacity generative models from few examples☆33Updated last year
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated last year
- Code from the article: "The Role of Disentanglement in Generalisation" (ICLR, 2021).☆22Updated 2 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆53Updated 5 years ago
- Implementation of Information Dropout☆39Updated 7 years ago
- Professor Forcing, NIPS'16☆45Updated 7 years ago
- Estimating Gradients for Discrete Random Variables by Sampling without Replacement☆39Updated 4 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- ☆61Updated last year
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- BIVA: A Very Deep Hierarchy of Latent Variables forGenerative Modeling☆29Updated 5 years ago
- Pytorch implementation of SCAN: Learning Abstract Hierarchical Compositional Visual Concepts☆21Updated 6 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆31Updated 4 years ago
- Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…☆62Updated 4 years ago