Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)
☆38Apr 25, 2017Updated 9 years ago
Alternatives and similar repositories for ars-reparameterization
Users that are interested in ars-reparameterization are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- implementation of different Dirichlet Variational Autoencoder Topic Models in Tensorflow☆49Feb 20, 2023Updated 3 years ago
- ☆11Mar 9, 2018Updated 8 years ago
- Chainer implementation of the paper Robust Conditional Generative Adversarial Networks☆15Jul 28, 2020Updated 5 years ago
- VAEs on Sparse Data☆12Oct 15, 2017Updated 8 years ago
- Learn models that are robust to spurious correlations in the dataset.☆26Dec 31, 2019Updated 6 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- UI for Dynamic Memory Networks☆14Apr 9, 2016Updated 10 years ago
- ☆12Dec 8, 2022Updated 3 years ago
- Variational Factorization Machines☆17Dec 20, 2016Updated 9 years ago
- Variational Dirichlet Process Gaussian Mixture Models☆29Feb 2, 2015Updated 11 years ago
- Efficient implementation of Generative Stochastic Networks☆12Nov 28, 2013Updated 12 years ago
- Non-parametric Bayesian in Python, including Indian buffet process (IBP), hierarchical Dirichlet process (HDP).☆73Sep 25, 2015Updated 10 years ago
- Variational inference for Dirichlet process mixture models with multinomial mixture components.☆37Jan 15, 2014Updated 12 years ago
- ☆30Oct 7, 2022Updated 3 years ago
- investigating use of variational auto encoders with multinomial latent variables for unsupervised data.☆25Jun 12, 2017Updated 8 years ago
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆67Apr 29, 2019Updated 7 years ago
- A PyTorch Implementation of VaDE(https://arxiv.org/pdf/1611.05148.pdf)☆39Jan 6, 2021Updated 5 years ago
- ☆31Oct 26, 2020Updated 5 years ago
- Develop tools for ensemble Kalman filter☆11Oct 16, 2019Updated 6 years ago
- ☆17Jan 5, 2018Updated 8 years ago
- PyTorch implementation of AVITM☆158Jul 14, 2018Updated 7 years ago
- Molcas wavefunction assistent☆13Jul 2, 2021Updated 4 years ago
- Official implementation of "Physics-Informed Long-Sequence Forecasting From Multi-Resolution Spatiotemporal Data".☆10Dec 12, 2022Updated 3 years ago
- Deep Large-Scale Inference UsingKnockoffs☆10Nov 4, 2021Updated 4 years ago
- Simple, predictable pricing with DigitalOcean hosting • AdAlways know what you'll pay with monthly caps and flat pricing. Enterprise-grade infrastructure trusted by 600k+ customers.
- A ssh plugin for shelljs☆10May 27, 2019Updated 6 years ago
- Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods☆13Nov 29, 2017Updated 8 years ago
- Generative models and other stuff too, maybe, perhaps even probably☆16Dec 12, 2015Updated 10 years ago
- Collapsed Variational Bayes☆72Sep 27, 2019Updated 6 years ago
- Tensorflow implementation for prodLDA and NVLDA.☆256Apr 19, 2021Updated 5 years ago
- KERAS: Multimodal Deep Learning for Semantic Segmentation (RGB, NIR Streams) - multiple architectures☆11Jun 19, 2017Updated 8 years ago
- Observe the dataset of images and targets in few shots☆11Sep 27, 2022Updated 3 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆38May 30, 2019Updated 6 years ago
- [SDM24] Official code for "Time-Transformer"☆18Sep 30, 2025Updated 7 months ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- Minicourse on Machine Learning for Many-Body Physics, Sept 25 – 29, 2017 São Paulo, Brazil☆21Sep 28, 2017Updated 8 years ago
- Markov Chain Monte Carlo (MCMC) and importance sampling in the context of Bayesian linear regression☆11Feb 25, 2018Updated 8 years ago
- Variational Auto-encoder with Non-parametric Bayesian Prior☆44May 18, 2017Updated 8 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52May 14, 2021Updated 4 years ago
- Tools for the symbolic manipulation of PyMC models, Theano, and TensorFlow graphs.☆65Mar 20, 2024Updated 2 years ago
- ☆11Aug 22, 2023Updated 2 years ago
- ☆10Nov 18, 2022Updated 3 years ago