Alternatives and similar repositories for whyshift

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

• huaxiuyao / Wild-Time
  Benchmark for Natural Temporal Distribution Shift (NeurIPS 2022)
  ☆67Updated 2 years ago
• LJSthu / HRM
  The code for the paper 'Heterogeneous Risk Minimization' of ICML2021.
  ☆25Updated 3 years ago
• IRMBed / IRMBed
  This is the project for IRM methods
  ☆12Updated 3 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
• LFhase / PAIR
  [ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization
  ☆53Updated last year
• opendataval / opendataval
  OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)
  ☆99Updated 5 months ago
• weitianxin / awesome-distribution-shift
  A curated list of papers and resources about the distribution shift in machine learning.
  ☆121Updated last year
• anzhang314 / ReScore
  Official code of "Boosting Differentiable Causal Discovery via Adaptive Sample Reweighting" (2023 ICLR)
  ☆16Updated 2 years ago
• LJSthu / Kernelized-HRM
  The code for our NeurIPS 2021 paper "Kernelized Heterogeneous Risk Minimization".
  ☆13Updated 3 years ago
• patrickrchao / DiffusionBasedCausalModels
  ☆26Updated 2 months ago
• facebookresearch / CausalRepID
  Experiments to reproduce results in Interventional Causal Representation Learning.
  ☆24Updated 2 years ago
• xwshen51 / DEAR
  Disentangled gEnerative cAusal Representation (DEAR)
  ☆60Updated 2 years ago
• changliu00 / causal-semantic-generative-model
  Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution …
  ☆74Updated 3 years ago
• TjuJianyu / RFC
  ☆12Updated last year
• ecreager / eiil
  Code for Environment Inference for Invariant Learning (ICML 2021 Paper)
  ☆50Updated 4 years ago
• ysharma1126 / ssl_identifiability
  Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
  ☆52Updated 3 years ago
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆84Updated last year
• vios-s / DiffAN
  Diffusion Models for Causal Discovery
  ☆85Updated 2 years ago
• zalanborsos / bilevel_coresets
  Coresets via Bilevel Optimization
  ☆66Updated 4 years ago
• ynysjtu / ood_bench
  ☆49Updated 2 years ago
• Wang-ML-Lab / bayesian-peft
  [NeurIPS 2024] BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models
  ☆28Updated 5 months ago
• anniesch / surgical-finetuning
  Code for "Surgical Fine-Tuning Improves Adaptation to Distribution Shifts" published at ICLR 2023
  ☆28Updated 2 years ago
• reds-lab / LAVA
  This is an official repository for "LAVA: Data Valuation without Pre-Specified Learning Algorithms" (ICLR2023).
  ☆48Updated last year
• thudzj / NeuralEigenFunction
  ☆16Updated 3 years ago
• LFhase / FeAT
  [NeurIPS 2023] Understanding and Improving Feature Learning for Out-of-Distribution Generalization
  ☆30Updated last month
• xu-ji / information-bottleneck
  Deep Learning & Information Bottleneck
  ☆61Updated 2 years ago
• MaximeRobeyns / bayesian_lora
  Bayesian Low-Rank Adaptation for Large Language Models
  ☆34Updated last year
• fedebotu / ICLR2023-OpenReviewData
  Crawl & Visualize ICLR 2023 Data from OpenReview
  ☆84Updated 2 years ago
• mkofinas / neural-graphs
  Official source code for "Graph Neural Networks for Learning Equivariant Representations of Neural Networks". In ICLR 2024 (oral).
  ☆81Updated 11 months ago
• huaxiuyao / C-Mixup
  C-Mixup for NeurIPS 2022
  ☆70Updated last year