Alternatives and similar repositories for HKBUthesis

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

• shenlei515 / VHL-paddle
  translation of VHL repo in paddle
  ☆25Updated 2 years ago
• warriors-30 / SFAT-paddle
  ☆24Updated 2 years ago
• Out-of-Distribution-Generalization / Out-of-Distribution-Generalization.github.io
  ☆26Updated 3 years ago
• 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.
  ☆62Updated 4 years ago
• Viperccc / RDIA
  ☆18Updated 3 years ago
• justincui03 / dc_benchmark
  ☆89Updated 3 years ago
• xiaoboxia / CDR
  ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels
  ☆78Updated 4 years ago
• AndrewZhou924 / MC-GRA
  [ICML 2023] "On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation"
  ☆23Updated 2 years ago
• linyongver / Bayesian-Invariant-Risk-Minmization
  This is the code for the paper Bayesian Invariant Risk Minmization of CVPR 2022.
  ☆47Updated 2 years ago
• xiaoboxia / Part-dependent-label-noise
  NeurIPS'2020: Part-dependent Label Noise: Towards Instance-dependent Label Noise
  ☆61Updated 5 years ago
• tmllab / 2023_ICLR_Moderate-DS
  ☆31Updated 2 years ago
• YonggangZhangUSTC / CausalAdv
  Code for 'CausalAdv: Adversarial Robustness Through the Lens of Causality'
  ☆43Updated 2 years ago
• tmlr-group / MC-GRA
  [ICML 2023] "On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation"
  ☆33Updated 2 years ago
• xiaoboxia / T-Revision
  NeurIPS'2019: Are Anchor Points Really Indispensable in Label-Noise Learning?
  ☆100Updated 4 years ago
• LYang-666 / TRGP
  [ICLR 2022] Official Code Repository for "TRGP: TRUST REGION GRADIENT PROJECTION FOR CONTINUAL LEARNING"
  ☆22Updated 3 years ago
• bhanML / label-noise-papers
  An update-to-date list for papers related with label-noise representation learning is here.
  ☆91Updated 4 years ago
• LFhase / PAIR
  [ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization
  ☆54Updated last year
• hehaodele / CIDA
  [ICML 2020] Continuously Indexed Domain Adaptation
  ☆121Updated 3 years ago
• ryokamoi / pytorch_influence_functions
  This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence…
  ☆17Updated 5 years ago
• skzhang1 / IDEAL
  IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models
  ☆59Updated 2 years ago
• a5507203 / Instance-dependent-Label-noise-Learning-under-a-Structural-Causal-Model
  ☆17Updated 2 years ago
• Wuyxin / DISC
  (ICML 2023) Discover and Cure: Concept-aware Mitigation of Spurious Correlation
  ☆43Updated 2 months ago
• NeuralCollapseApplications / ImbalancedLearning
  [NeurIPS 2022] The official code for our NeurIPS 2022 paper "Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnab…
  ☆49Updated 3 years ago
• ynysjtu / ood_bench
  ☆49Updated 3 years ago
• tmlr-group / G-effect
  [ICLR 2025] "Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond"
  ☆17Updated 11 months ago
• princetonvisualai / RememberThePast-DatasetDistillation
  ☆41Updated 3 years ago
• x-zho14 / MAPLE
  Code for Model Agnostic Sample Reweighting for Out-of-Distribution Learning
  ☆45Updated 2 years ago
• QizhouWang / DOE
  ☆26Updated 2 years ago
• OPTML-Group / Unlearn-Sparse
  [NeurIPS23 (Spotlight)] "Model Sparsity Can Simplify Machine Unlearning" by Jinghan Jia*, Jiancheng Liu*, Parikshit Ram, Yuguang Yao, Gao…
  ☆82Updated last year
• a5507203 / dual-t-reducing-estimation-error-for-transition-matrix-in-label-noise-learning
  ☆15Updated 2 years ago