mbp28 / determinantal-point-processesLinks
Determinantal Point Processes in Python (NumPy)
☆25Updated 8 years ago
Alternatives and similar repositories for determinantal-point-processes
Users that are interested in determinantal-point-processes are comparing it to the libraries listed below
Sorting:
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 6 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 5 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago
- The Variational Homoencoder: Learning to learn high capacity generative models from few examples☆34Updated 2 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 5 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference"☆121Updated 7 years ago
- Code for the "Neural Expectation Maximization" paper.☆126Updated 2 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆49Updated 7 years ago
- Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018☆43Updated 6 years ago
- [ICLR 2019] Learning Representations of Sets through Optimized Permutations☆36Updated 6 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆112Updated 6 years ago
- Implementation of iterative inference in deep latent variable models☆43Updated 6 years ago
- Implementation of Conditionally Shifted Neurons by Munkhdalai et al. (https://arxiv.org/pdf/1712.09926.pdf)☆28Updated 7 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 7 years ago
- Deep convolutional gaussian processes.☆80Updated 6 years ago
- A Tensorfflow implementation of Attend, Infer, Repeat☆81Updated 6 years ago
- Code for the paper "Learning sparse transformations through backpropagation"☆43Updated 5 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Implementation of paper "GibbsNet: Iterative Adversarial Inference for Deep Graphical Models" in PyTorch☆57Updated 7 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- ZForcing Repo☆40Updated 7 years ago
- Lua implementation of Entropy-SGD☆82Updated 7 years ago
- Deep Generative Models with Stick-Breaking Priors☆96Updated 9 years ago
- PyTorch implementation of PathNet: Evolution Channels Gradient Descent in Super Neural Networks☆80Updated 7 years ago
- Autoregressive Energy Machines☆78Updated 2 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆54Updated 6 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago