ahmedmalaa / evaluating-generative-modelsLinks
☆22Updated 2 years ago
Alternatives and similar repositories for evaluating-generative-models
Users that are interested in evaluating-generative-models are comparing it to the libraries listed below
Sorting:
- Deep direct likelihood knockoffs☆12Updated 4 years ago
- ☆18Updated last year
- Adaptive and Reliable Classification: efficient conformity scores for multi-class classification problems☆33Updated 2 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆35Updated 4 years ago
- ☆29Updated 3 years ago
- ☆11Updated 2 years ago
- [NeurIPS 2023] Riemannian Residual Neural Networks (https://arxiv.org/abs/2006.10254)☆22Updated last year
- ☆18Updated 2 years ago
- NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks☆37Updated 2 years ago
- Code for our ICLR19 paper "Wasserstein Barycenters for Model Ensembling", Pierre Dognin, Igor Melnyk, Youssef Mroueh, Jarret Ross, Cicero…☆23Updated 6 years ago
- Local explanations with uncertainty 💐!☆42Updated 2 years ago
- Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'☆18Updated 2 years ago
- Diffusion Models for Causal Discovery☆90Updated 2 years ago
- A Pytorch implementation of missing data imputation using optimal transport.☆105Updated 4 years ago
- Python-based persistent homology algorithms☆19Updated 2 years ago
- Code for the paper 'Continual Learning via Sequential Function-Space Variational Inference'☆25Updated 2 years ago
- Bayesian optimization with conformal coverage guarantees☆29Updated 3 years ago
- Unifying Multimodal Variational Autoencoders (VAEs) in Pytorch☆62Updated last month
- Official repository for Cell Attention Networks☆14Updated last year
- Official repository for the ICLR 2022 paper "Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions"…☆14Updated 3 years ago
- ☆18Updated 3 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆45Updated 2 years ago
- VAEs and nonlinear ICA: a unifying framework☆39Updated 5 years ago
- ☆11Updated 4 months ago
- Efficient Conditionally Invariant Representation Learning (ICLR 2023, Oral)☆21Updated 3 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated 2 years ago
- Tensorflow implementation for the SVGP-VAE model.☆22Updated 4 years ago
- Codebase for SEFS: Self-Supervision Enhanced Feature Selection with Correlated Gates☆24Updated 2 years ago
- Official implementation of Joint Multidimensional Scaling☆23Updated 2 years ago
- Pacmed Labs experiments on uncertainty estimation, focusing on unbalanced tabular data and classification tasks.☆21Updated 4 years ago