Alternatives and similar repositories for CAGrad

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

• lorenmt / auto-lambda
  The Implementation of "Auto-Lambda: Disentangling Dynamic Task Relationships" [TMLR 2022].
  ☆135Updated 2 years ago
• AvivNavon / nash-mtl
  Official implementation of "Multi-Task Learning as a Bargaining Game" [ICML 2022]
  ☆225Updated last year
• tianheyu927 / PCGrad
  Code for "Gradient Surgery for Multi-Task Learning"
  ☆325Updated 5 years ago
• WeiChengTseng / Pytorch-PCGrad
  Pytorch reimplementation for "Gradient Surgery for Multi-Task Learning"
  ☆348Updated 4 years ago
• AI-secure / multi-task-learning
  Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation", Haoxi…
  ☆68Updated 3 years ago
• Cranial-XIX / FAMO
  Official PyTorch Implementation for Fast Adaptive Multitask Optimization (FAMO)
  ☆90Updated last year
• sunxm2357 / AdaShare
  AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning
  ☆112Updated 4 years ago
• Pengxin-Guo / Awesome-Multi-Task-Learning
  Paper List for Multi-Task Learning (focus on architectures and optimization for MTL)
  ☆47Updated last year
• mit-gfx / ContinuousParetoMTL
  [ICML 2020] Efficient Continuous Pareto Exploration in Multi-Task Learning
  ☆145Updated 3 years ago
• adrianjav / rotograd
  Official Pytorch's implementation of RotoGrad
  ☆78Updated last year
• ShiYunyi / Meta-Weight-Net_Code-Optimization
  A new code framework that uses pytorch to implement meta-learning, and takes Meta-Weight-Net as an example.
  ☆60Updated 3 years ago
• Xi-L / ParetoMTL
  Code for Neural Information Processing Systems (NeurIPS) 2019 paper: Pareto Multi-Task Learning
  ☆138Updated 5 years ago
• chrhenning / hypercl
  Continual Learning with Hypernetworks. A continual learning approach that has the flexibility to learn a dedicated set of parameters, fin…
  ☆164Updated 3 years ago
• mominabbass / Sharp-MAML
  Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning
  ☆31Updated 2 years ago
• thuml / ForkMerge
  Code release of paper "ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning" (NeurIPS 2023)
  ☆17Updated last year
• woozch / PCGrad-pytorch-example
  PCGrad pytorch sample code [not official]
  ☆32Updated 5 years ago
• AvivNavon / AuxiLearn
  Official implementation of Auxiliary Learning by Implicit Differentiation [ICLR 2021]
  ☆84Updated 11 months ago
• yangsenius / learning-to-learn-by-pytorch
  "Learning to learn by gradient descent by gradient descent "by PyTorch -- a simple re-implementation.
  ☆60Updated 5 years ago
• tstandley / taskgrouping
  Code for Which Tasks Should Be Learned Together in Multi-task Learning?
  ☆97Updated 2 years ago
• ryanchankh / mcr2
  Official Implementation of Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction (2020)
  ☆199Updated 2 years ago
• kashif / ICLR2022-OpenReviewData
  Crawl & visualize ICLR papers and reviews.
  ☆107Updated 3 years ago
• YugeTen / fish
  Official implementation of paper Gradient Matching for Domain Generalization
  ☆122Updated 3 years ago
• xiaofangxd / Multi-objective-optimization-and-Multi-task-Learning
  ☆73Updated 9 months ago
• yuanli2333 / CKA-Centered-Kernel-Alignment
  Reproduce CKA: Similarity of Neural Network Representations Revisited
  ☆304Updated 5 years ago
• 1Konny / VIB-pytorch
  Pytorch implementation of Deep Variational Information Bottleneck
  ☆195Updated 7 years ago
• xjtushujun / meta-weight-net
  NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).
  ☆289Updated 3 years ago
• Johswald / learning_where_to_learn
  ☆38Updated 7 months ago
• weigq / iclr2022_stats
  ☆46Updated 2 years ago
• gnobitab / MultiObjectiveSampling
  ☆17Updated 3 years ago
• wrh14 / online_adaptation_to_label_distribution_shift
  Code repo for the NeurIPS 2021 paper "Online Adaption to Label Distribution Shift".
  ☆15Updated 2 years ago