Alternatives and similar repositories for evaluating-generative-models:

Users that are interested in evaluating-generative-models are comparing it to the libraries listed below

• rajesh-lab / ddlk
  Deep direct likelihood knockoffs
  ☆12Updated 4 years ago
• EtashGuha / R2CCP
  ☆22Updated last year
• chl8856 / SEFS
  Codebase for SEFS: Self-Supervision Enhanced Feature Selection with Correlated Gates
  ☆23Updated last year
• vanderschaarlab / MIRACLE
  ☆27Updated last year
• facebookresearch / CausalRepID
  Experiments to reproduce results in Interventional Causal Representation Learning.
  ☆24Updated 2 years ago
• msesia / arc
  Adaptive and Reliable Classification: efficient conformity scores for multi-class classification problems
  ☆31Updated 2 years ago
• vios-s / Diff-SCM
  Code for Diff-SCM paper
  ☆96Updated last year
• vios-s / DiffAN
  Diffusion Models for Causal Discovery
  ☆85Updated 2 years ago
• clementchadebec / Data_Augmentation_with_VAE-DALI
  ☆18Updated 3 years ago
• clarafy / conformal-for-design
  ☆30Updated 2 years ago
• pfnet-research / TabCSDI
  A code for the NeurIPS 2022 Table Representation Learning Workshop paper: "Diffusion models for missing value imputation in tabular data"
  ☆48Updated 10 months ago
• mlfoundations / tableshift
  A benchmark for distribution shift in tabular data
  ☆52Updated 10 months ago
• sanatonek / time_series_explainability
  ☆60Updated 4 years ago
• BorgwardtLab / ggme
  Official repository for the ICLR 2022 paper "Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions"…
  ☆14Updated 2 years ago
• adrianjav / heterogeneous_vaes
  Pytorch implementation of VAEs for heterogeneous likelihoods.
  ☆42Updated 2 years ago
• gulnazaki / counterfactual-benchmark
  Benchmark study of quality and faithfulness of counterfactual image generation
  ☆21Updated last month
• vanderschaarlab / evaluating-generative-models
  ☆29Updated 2 years ago
• AIgen / df-posthoc-calibration
  Model-agnostic posthoc calibration without distributional assumptions
  ☆42Updated last year
• philipdarke / torchtime
  Benchmark time series data sets for PyTorch
  ☆35Updated last year
• ucr-optml / AutoBalance
  ☆15Updated 3 years ago
• ahmedmalaa / Fourier-flows
  ☆18Updated 3 years ago
• a-norcliffe / Composite-Feature-Selection
  Official Code for the paper: "Composite Feature Selection using Deep Ensembles"
  ☆22Updated 2 years ago
• MLforHealth / ClinicalDG
  An Empirical Framework for Domain Generalization In Clinical Settings
  ☆30Updated 3 years ago
• zzzace2000 / nodegam
  Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"
  ☆45Updated 2 years ago
• boschresearch / GMM_DAE
  ☆20Updated 3 years ago
• Pacmed / ehr_ood_detection
  Pacmed Labs experiments on uncertainty estimation, focusing on unbalanced tabular data and classification tasks.
  ☆21Updated 3 years ago
• rpatrik96 / nl-causal-representations
  This is the code for the paper Jacobian-based Causal Discovery with Nonlinear ICA, demonstrating how identifiable representations (partic…
  ☆18Updated 7 months ago
• ggbioing / mcvae
  Multi-Channel Variational Auto Encoder: A Bayesian Deep Learning Framework for Modeling High-Dimensional Heterogeneous Data.
  ☆33Updated 4 years ago
• JakobHavtorn / hvae-oodd
  Official source code repository for the ICML 2021 paper "Hierarchical VAEs Know What They Don't Know"
  ☆30Updated 3 years ago
• lemeln / nam
  Neural Additive Models (Google Research)
  ☆28Updated 11 months ago