taDachs / Overview-of-Variational-Autoencoder-based-Generative-ModelsLinks
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
Sorting:
- ☆30Updated 5 years ago
- Source code for paper Conservative Uncertainty Estimation By Fitting Prior Networks (ICLR 2020)☆21Updated 2 years ago
- Monotone operator equilibrium networks☆53Updated 5 years ago
- ☆54Updated last year
- ☆64Updated last year
- repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE☆56Updated 4 years ago
- Experiments for Meta-Learning Symmetries by Reparameterization☆57Updated 4 years ago
- PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows☆31Updated 4 years ago
- [NeurIPS'20] Code for the Paper Compositional Visual Generation and Inference with Energy Based Models☆46Updated 2 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'☆26Updated 4 years ago
- Hybrid Discriminative-Generative Training via Contrastive Learning☆75Updated 2 years ago
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆69Updated 4 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆88Updated 3 years ago
- Repo reproducing experimental results in "Addressing the Topological Defects of Disentanglement"☆22Updated 3 years ago
- ☆21Updated 3 years ago
- Code for "Bridging the Gap between f-GANs and Wasserstein GANs", ICML 2020☆14Updated 5 years ago
- ☆22Updated 3 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561☆25Updated 4 years ago
- Limitations of the Empirical Fisher Approximation☆48Updated 7 months ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) p…☆41Updated 4 years ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆21Updated 6 years ago
- Code for "Accelerating Natural Gradient with Higher-Order Invariance"☆30Updated 6 years ago
- Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"☆49Updated 5 years ago
- code for "Semi-Discrete Normalizing Flows through Differentiable Tessellation"☆27Updated 2 years ago
- Code associated with our paper "Learning Group Structure and Disentangled Representations of Dynamical Environments"☆15Updated 2 years ago
- ☆13Updated 6 years ago