taDachs / Overview-of-Variational-Autoencoder-based-Generative-Models
This is an article about using variational autoencoders for the generation of new data. It contains the code for generating the plots and training the mentioned models on celeb_a.
☆12Updated 4 years ago
Alternatives and similar repositories for Overview-of-Variational-Autoencoder-based-Generative-Models:
Users that are interested in Overview-of-Variational-Autoencoder-based-Generative-Models are comparing it to the libraries listed below
- Source code for paper Conservative Uncertainty Estimation By Fitting Prior Networks (ICLR 2020)☆21Updated 2 years ago
- ☆31Updated 4 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 6 years ago
- Monotone operator equilibrium networks☆51Updated 4 years ago
- ☆53Updated 7 months ago
- Experiments for Meta-Learning Symmetries by Reparameterization☆56Updated 3 years ago
- Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561☆24Updated 3 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆27Updated 3 years ago
- Code release for the ICLR paper☆20Updated 6 years ago
- Code for "Bridging the Gap between f-GANs and Wasserstein GANs", ICML 2020☆14Updated 4 years ago
- ☆18Updated 3 years ago
- Variational Reinforcement Learning☆16Updated 7 months ago
- Code for "Training Deep Energy-Based Models with f-Divergence Minimization" ICML 2020☆36Updated last year
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- Code associated with our paper "Learning Group Structure and Disentangled Representations of Dynamical Environments"☆15Updated 2 years ago
- ☆13Updated 5 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated last week
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆48Updated 5 years ago
- Implementation of the Functional Neural Process models☆43Updated 4 years ago
- Estimating Gradients for Discrete Random Variables by Sampling without Replacement☆40Updated 5 years ago
- code for "Semi-Discrete Normalizing Flows through Differentiable Tessellation"☆26Updated 2 years ago
- PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows☆31Updated 3 years ago
- Natural Gradient, Variational Inference☆29Updated 5 years ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆20Updated 6 years ago
- JAX code for the paper "Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation"☆43Updated 3 years ago
- Code for Unbiased Implicit Variational Inference (UIVI)☆13Updated 6 years ago
- Riemannian Convex Potential Maps☆67Updated last year
- An adaptive training algorithm for residual network☆15Updated 4 years ago
- ☆29Updated 4 years ago