Alternatives and similar repositories for AutoBalance:

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

• mertyg / beyond-confidence-atypicality
  Repository for the NeurIPS 2023 paper "Beyond Confidence: Reliable Models Should Also Consider Atypicality"
  ☆12Updated last year
• ondrejbohdal / meta-calibration
  Official PyTorch implementation of "Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error"
  ☆34Updated last year
• AIgen / df-posthoc-calibration
  Model-agnostic posthoc calibration without distributional assumptions
  ☆42Updated last year
• yaoyao-liu / online-hyperparameter-optimization
  PyTorch implementation of "Online Hyperparameter Optimization for Class-Incremental Learning" (AAAI 2023 Oral)
  ☆17Updated last year
• zzzx1224 / EBTSA-ICLR2023
  ☆10Updated 2 months ago
• Vanint / Core-tuning
  This repository is the official implementation of Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regulari…
  ☆21Updated 2 years ago
• ahujak / IB-IRM
  ☆30Updated 3 years ago
• alexrame / fishr
  Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization
  ☆86Updated 2 years ago
• hsouri / BayesianTransferLearning
  ☆109Updated 2 years ago
• huaxiuyao / C-Mixup
  C-Mixup for NeurIPS 2022
  ☆70Updated last year
• LFhase / PAIR
  [ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization
  ☆53Updated last year
• jhaochenz96 / spectral_contrastive_learning
  ☆20Updated 3 years ago
• amazon-science / long-tailed-ood-detection
  Official implementation for "Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition" (I…
  ☆44Updated last year
• x-zho14 / MAPLE
  Code for Model Agnostic Sample Reweighting for Out-of-Distribution Learning
  ☆43Updated 2 years ago
• RenkunNi / MetaContrastive
  The official code for the publication: "The Close Relationship Between Contrastive Learning and Meta-Learning".
  ☆19Updated 2 years ago
• tqch / poisson-jump
  Official Implementation of Paper "Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling" (ICML 2023)
  ☆10Updated last year
• cambridge-mlg / CLUE
  Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"
  ☆35Updated last year
• xxgege / NICO-plus
  The Official Repository for CVPR2023 Paper "NICO++: Towards Better Benchmarking for Domain Generalization".
  ☆39Updated last year
• TjuJianyu / RFC
  ☆12Updated last year
• kakaobrain / irm-empirical-study
  An Empirical Study of Invariant Risk Minimization
  ☆27Updated 4 years ago
• mlfoundations / tableshift
  A benchmark for distribution shift in tabular data
  ☆52Updated 10 months ago
• aniruddhraghu / meta-pretraining
  Code accompanying paper: Meta-Learning to Improve Pre-Training
  ☆37Updated 3 years ago
• xu-ji / information-bottleneck
  Deep Learning & Information Bottleneck
  ☆60Updated last year
• Liuhong99 / EAML
  Code Release for Learning to Adapt to Evolving Domains
  ☆31Updated 3 years ago
• huaxiuyao / LISA
  LISA for ICML 2022
  ☆48Updated 2 years ago
• suinleelab / vit-shapley
  ☆33Updated 9 months ago
• Newbeeer / TRM
  Learning Representations that Support Robust Transfer of Predictors
  ☆20Updated 3 years ago
• TongtongFANG / DIW
  Code for the paper "Rethinking Importance Weighting for Deep Learning under Distribution Shift".
  ☆30Updated 4 years ago
• linyongver / ZIN_official
  This is the implementation for the NeurIPS 2022 paper: ZIN: When and How to Learn Invariance Without Environment Partition?
  ☆22Updated 2 years ago
• ecreager / eiil
  Code for Environment Inference for Invariant Learning (ICML 2021 Paper)
  ☆50Updated 3 years ago