Alternatives and similar repositories for doro:

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

• LJSthu / Kernelized-HRM
  The code for our NeurIPS 2021 paper "Kernelized Heterogeneous Risk Minimization".
  ☆12Updated 3 years ago
• yjhuangcd / local-lipschitz
  Official implementation for Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (NeurIPS, 2021).
  ☆23Updated 2 years ago
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆42Updated last year
• zalanborsos / bilevel_coresets
  Coresets via Bilevel Optimization
  ☆65Updated 4 years ago
• gnobitab / MultiObjectiveSampling
  ☆17Updated 3 years ago
• yaohungt / Pointwise_Dependency_Neural_Estimation
  ☆20Updated 4 years ago
• duchi-lab / certifiable-distributional-robustness
  Certifying Some Distributional Robustness with Principled Adversarial Training (https://arxiv.org/abs/1710.10571)
  ☆45Updated 7 years ago
• StanfordASL / moca
  ☆32Updated 2 years ago
• uiuctml / ISR
  Invariant-feature Subspace Recovery (ISR)
  ☆23Updated 2 years ago
• yaodongyu / ProjNorm
  Predicting Out-of-Distribution Error with the Projection Norm
  ☆17Updated 2 years ago
• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• TjuJianyu / RFC
  ☆12Updated last year
• AnonymousNIPS2019 / DeepnetHessian
  The Full Spectrum of Deepnet Hessians at Scale: Dynamics with SGD Training and Sample Size
  ☆17Updated 5 years ago
• facebookresearch / InvarianceUnitTests
  Toy datasets to evaluate algorithms for domain generalization and invariance learning.
  ☆42Updated 3 years ago
• mingzhang-yin / ARM-gradient
  Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)
  ☆28Updated 6 years ago
• ondrejbohdal / evograd
  Official PyTorch implementation of "EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization"
  ☆21Updated 3 years ago
• MadryLab / failure-directions
  Distilling Model Failures as Directions in Latent Space
  ☆46Updated 2 years ago
• BB-UCL / Lasagne
  ☆13Updated 6 years ago
• ssagawa / overparam_spur_corr
  An Investigation of Why Overparameterization Exacerbates Spurious Correlations
  ☆31Updated 4 years ago
• tml-epfl / understanding-sam
  Towards Understanding Sharpness-Aware Minimization [ICML 2022]
  ☆35Updated 2 years ago
• MadryLab / BREEDS-Benchmarks
  ☆55Updated 4 years ago
• ecreager / eiil
  Code for Environment Inference for Invariant Learning (ICML 2021 Paper)
  ☆50Updated 3 years ago
• deep-lab / DeepnetHessian
  Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians (ICML 2019)
  ☆17Updated 6 years ago
• tml-epfl / sharpness-vs-generalization
  A modern look at the relationship between sharpness and generalization [ICML 2023]
  ☆43Updated last year
• thudzj / ScalableBDL
  Code for "BayesAdapter: Being Bayesian, Inexpensively and Robustly, via Bayeisan Fine-tuning"
  ☆31Updated 9 months ago
• a7b23 / H-Divergence
  ☆21Updated 2 years ago
• mhw32 / meta-inference-public
  A PyTorch implementation of "Meta-Amortized Variational Inference and Learning" (https://arxiv.org/abs/1902.01950)
  ☆14Updated 5 years ago
• p-lambda / gradual_domain_adaptation
  ☆37Updated 4 years ago
• GiulsLu / Sinkhorn-Barycenters
  Sinkhorn Barycenters via Frank-Wolfe algorithm
  ☆25Updated 5 years ago
• Shen-Lab / Bayesian-L2O
  [ICLR 2022] "Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How" by Yuning You, Yue Cao, Tianl…
  ☆14Updated 2 years ago