Alternatives and similar repositories for remasker

Users that are interested in remasker are comparing it to the libraries listed below

• AIgen / df-posthoc-calibration
  Model-agnostic posthoc calibration without distributional assumptions
  ☆42Updated last year
• MLforHealth / ClinicalDG
  An Empirical Framework for Domain Generalization In Clinical Settings
  ☆30Updated 3 years ago
• BorisMuzellec / MissingDataOT
  A Pytorch implementation of missing data imputation using optimal transport.
  ☆101Updated 3 years ago
• vanderschaarlab / Datagnosis
  A Data-Centric library providing a unified interface for state-of-the-art methods for hardness characterisation of data points.
  ☆24Updated 2 months ago
• mlfoundations / tableshift
  A benchmark for distribution shift in tabular data
  ☆52Updated 11 months ago
• iancovert / shapley-regression
  For calculating Shapley values via linear regression.
  ☆67Updated 3 years ago
• cambridge-mlg / CLUE
  Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"
  ☆35Updated last year
• FabianFalck / mfcvae
  Official PyTorch implementation of 🏁 MFCVAE 🏁: "Multi-Facet Clustering Variatonal Autoencoders (MFCVAE)" (NeurIPS 2021). A class of var…
  ☆40Updated last year
• zzzace2000 / nodegam
  Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"
  ☆46Updated 2 years ago
• YyzHarry / SubpopBench
  [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift
  ☆108Updated last year
• vanderschaarlab / DECAF
  DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks
  ☆20Updated 2 years ago
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆35Updated 4 years ago
• QingyuZhao / BR-Net
  ☆46Updated 4 years ago
• mertyg / beyond-confidence-atypicality
  Repository for the NeurIPS 2023 paper "Beyond Confidence: Reliable Models Should Also Consider Atypicality"
  ☆13Updated last year
• alextamkin / active-learning-pretrained-models
  Active Learning Helps Pretrained Models Learn the Intended Task (https://arxiv.org/abs/2204.08491) by Alex Tamkin, Dat Nguyen, Salil Desh…
  ☆11Updated 2 years ago
• jlko / active-testing
  Active and Sample-Efficient Model Evaluation
  ☆24Updated 4 years ago
• betacal / python
  Beta calibration
  ☆29Updated last year
• zhang64-llnl / Mix-n-Match-Calibration
  ☆35Updated 4 years ago
• ModelOriented / metaMIMIC
  ☆12Updated 2 years ago
• i6092467 / vadesc
  A probabilistic model to cluster survival data in a variational deep clustering setting
  ☆30Updated 2 years ago
• psanch21 / VACA
  ☆23Updated 2 years ago
• cianeastwood / qrm
  Quantile risk minimization
  ☆24Updated 9 months ago
• ramneetk / iDECODe
  AAAI, 2022
  ☆8Updated 6 months ago
• oscarkey / explanations-by-minimizing-uncertainty
  Code for "Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties"
  ☆18Updated 4 years ago
• vios-s / DiffAN
  Diffusion Models for Causal Discovery
  ☆85Updated 2 years ago
• AlvinWen428 / FeatureCP
  The official codebase for Predictive Inference with Feature Conformal Prediction
  ☆34Updated 2 years ago
• vios-s / Diff-SCM
  Code for Diff-SCM paper
  ☆96Updated last year
• ys-zong / MEDFAIR
  [ICLR 2023 spotlight] MEDFAIR: Benchmarking Fairness for Medical Imaging
  ☆63Updated last year
• CAMP-eXplain-AI / Style-CheXplain
  GAN-based method to create counterfactual explanations for chest X-rays
  ☆24Updated 2 years ago
• CompML / survey-distribution-shift
  Survey for Distribution Shift
  ☆19Updated 3 years ago