DPBayes / d3pLinks
An implementation of the differentially private variational inference algorithm for NumPyro.
☆16Updated last year
Alternatives and similar repositories for d3p
Users that are interested in d3p are comparing it to the libraries listed below
Sorting:
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆78Updated last year
- Composable kernels for scikit-learn implemented in JAX.☆45Updated 5 years ago
- Code for fast dpsgd implementations in JAX/TF☆60Updated 3 years ago
- Python implementation of smooth optimal transport.☆61Updated 4 years ago
- Variational inference for hierarchical dynamical systems☆49Updated last year
- Auxiliary variable Markov chain Monte Carlo methods☆10Updated 8 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 4 years ago
- ☆17Updated 7 years ago
- ☆31Updated 3 years ago
- Code for our ICLR Trustworthy ML 2020 workshop paper "Improved Image Wasserstein Attacks and Defenses"☆14Updated 5 years ago
- ☆16Updated 2 years ago
- #UAI2020 Codes for PAC-Bayesian Contrastive Unsupervised Representation Learning☆13Updated 3 years ago
- ☆51Updated last year
- Scalable Bayes via Barycenter in Wasserstein Space☆10Updated 8 years ago
- (ICML 2021) Mandoline: Model Evaluation under Distribution Shift☆30Updated 4 years ago
- A clean TensorFlow implementation of Concrete Dropout☆22Updated 7 years ago
- A comparison of the dimensionality reduction results using t-SNE, UMAP, PCA, and TriMap☆29Updated 3 years ago
- ☆10Updated 4 years ago
- The Shape of Data: Intrinsic Distance for Comparing Data Distributions☆12Updated 6 years ago
- ☆11Updated 3 years ago
- Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)☆14Updated 6 years ago
- Learning generative models with Sinkhorn Loss☆30Updated 7 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆26Updated 5 years ago
- The Union of Intersections Framework in Python☆15Updated 3 weeks ago
- Bayesian and Maximum Likelihood Implementation of the Normalizing Flow Network (NFN): https://arxiv.org/abs/1907.08982☆22Updated 5 years ago
- Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding☆24Updated 3 years ago
- Random feature latent variable models in Python☆23Updated 2 years ago
- Repo reproducing experimental results in "Addressing the Topological Defects of Disentanglement"☆22Updated 3 years ago
- Investigate the speed of adaptation of structural causal models☆15Updated 4 years ago