bhanML

bhanML's Stars

• graph4ai/graph4nlp

  Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. Welcome to visit our DLG4NLP website (https://dlg4nlp.github.io/index.html) for various learning resources!

  Language:Python1.7k30172202

• dustinvtran/latex-templates

  A collection of LaTeX templates used for research, courses, and miscellanea.

  Language:TeX747202151

• P2333/Papers-of-Robust-ML

  Related papers for robust machine learning

  56543155

• yaodongyu/TRADES

  TRADES (TRadeoff-inspired Adversarial DEfense via Surrogate-loss minimization)

  Language:Python5231028124

• bhanML/Co-teaching

  NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels

  Language:Python4941211105

• uber-research/learning-to-reweight-examples

  Code for paper "Learning to Reweight Examples for Robust Deep Learning"

  Language:Python269101252

• 2prime/ODE-DL

  Paper List For Linking ODE and Deep Learning

  24519221

• zjfheart/Friendly-Adversarial-Training

  Attacks Which Do Not Kill Training Make Adversarial Learning Stronger (ICML2020 Paper)

  Language:Python1265330

• MediaBrain-SJTU/BCL

  [ICML2022] Contrastive Learning with Boosted Memorization

  Language:Python111448

• xiaoboxia/T-Revision

  NeurIPS'2019: Are Anchor Points Really Indispensable in Label-Noise Learning?

  Language:Python975018

• xingruiyu/coteaching_plus

  ICML'19 How does Disagreement Help Generalization against Label Corruption?

  Language:Python834716

• bhanML/Masking

  NeurIPS'18: Masking: A New Perspective of Noisy Supervision

  Language:Python54507

• kristery/Imitation-Learning-from-Imperfect-Demonstration

  [ICML 2019] Implementation of "Imitation Learning from Imperfect Demonstration"

  Language:Python462112

• ZFancy/SFAT

  [ICLR 2023] "Combating Exacerbated Heterogeneity for Robust Models in Federated Learning"

  Language:Python28217

• shenlei515/VHL-paddle

  translation of VHL repo in paddle

  Language:Python25100

• warriors-30/SFAT-paddle

  Language:Python24100

• Sjtubrian/SAMMD

  This is the source code for Maximum Mean Discrepancy Test is Aware of Adversarial Attacks (ICML2021).

  Language:Python19324

• voot-t/vild_code

  Source code of "Variational Imitation Learning with Diverse-quality Demonstrations" in ICML 2020. This github repository includes python code and datasets used in the experiments.

  Language:Python19223

• quanmingyao/FasTer

  Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations. ICML-2019.

  Language:MATLAB16307

• Ferenas/CAVL

  Exploiting Class Activation Value for Partial-Label Learning, ICLR 2022 (poster)

  Language:Python14112

• a5507203/dual-t-reducing-estimation-error-for-transition-matrix-in-label-noise-learning

  Language:Python124

• QizhouWang/MAIL

  source code for NeurIPS21 paper robabilistic Margins for Instance Reweighting in Adversarial Training

  Language:Python10101

• Haoang97/TOHAN

  Source code for NeurIPS 2021 paper "TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation".

  Language:Python9114

• QizhouWang/instance-dependent-label-noise

  Language:Python9101

• Sunarker/Safeguarded-Dynamic-Label-Regression-for-Noisy-Supervision

  Language:Python9372

• zjfheart/Robust-ResNet

  Towards Robust ResNet: A Small Step but a Giant Leap (IJCAI 2019)

  Language:Python8213

• d12306/dsnet

  Code for ICML'21 paper Learning Diverse-Structured Networks for Adversarial Robustness

  Language:Python6112

• QizhouWang/Max-Matching

  Language:Python4101

• Sunarker/LCCN

  Latent Class-Conditional Noise Model

  Language:Python4201

• bhanML/Robust-ResNet

  IJCAI'19: Towards Robust ResNet: A Small Step but a Giant Leap

  Language:Python1000