wgao9 / mixed_KSGLinks
☆38Updated 7 years ago
Alternatives and similar repositories for mixed_KSG
Users that are interested in mixed_KSG are comparing it to the libraries listed below
Sorting:
- ☆40Updated 6 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆84Updated 4 years ago
- Classifier Conditional Independence Test: A CI test that uses a binary classifier (XGBoost) for CI testing☆45Updated last year
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆63Updated 7 years ago
- Fair Empirical Risk Minimization (FERM)☆37Updated 4 years ago
- Deep Neural Networks Entropy from Replicas☆32Updated 5 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 5 years ago
- Variational Fourier Features☆85Updated 3 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)☆22Updated 3 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆77Updated last year
- Code for doubly stochastic gradients☆25Updated 10 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"☆71Updated 8 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 2 years ago
- Code for "Towards a learning theory of cause-effect inference" (ICML 2015).☆30Updated 4 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- General Latent Feature Modeling for Heterogeneous data☆49Updated last year
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆39Updated 3 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 4 years ago
- ☆43Updated 6 years ago
- A clean TensorFlow implementation of Concrete Dropout☆22Updated 7 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆113Updated 6 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 8 years ago
- Implicit generative models and related stuff based on the MMD, in PyTorch☆16Updated 4 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago