Alternatives and similar repositories for NeurIPS2022_UOT_fine_tuning:

Users that are interested in NeurIPS2022_UOT_fine_tuning are comparing it to the libraries listed below

• VITA-Group / MAK
  [NeurIPS 2021] “Improving Contrastive Learning on Imbalanced Data via Open-World Sampling”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangya…
  ☆28Updated 3 years ago
• WOWNICE / ssl-small
  Code implementation for paper "On the Efficacy of Small Self-Supervised Contrastive Models without Distillation Signals".
  ☆16Updated 3 years ago
• anshuman23 / InfDataSel
  Code for paper: “What Data Benefits My Classifier?” Enhancing Model Performance and Interpretability through Influence-Based Data Selecti…
  ☆22Updated 10 months ago
• kaidic / HAR
  [ICLR 2021] Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization
  ☆40Updated 3 years ago
• IBM / model-reprogramming
  Repository for research works and resources related to model reprogramming <https://arxiv.org/abs/2202.10629>
  ☆61Updated last year
• Piyush-555 / GaussianDistillation
  Data-free knowledge distillation using Gaussian noise (NeurIPS paper)
  ☆15Updated 2 years ago
• Kthyeon / FINE_official
  NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"
  ☆39Updated 3 years ago
• TencentARC / SFDA
  ☆21Updated 2 years ago
• chingyaoc / RINCE
  CVPR 2022, Robust Contrastive Learning against Noisy Views
  ☆83Updated 3 years ago
• salesforce / RRL
  ☆17Updated 3 years ago
• tianyizhou / DoCL
  Paper and Code for "Curriculum Learning by Optimizing Learning Dynamics" (AISTATS 2021)
  ☆19Updated 3 years ago
• yfzhang114 / AdaNPC
  This is an official PyTorch implementation of the ICML 2023 paper AdaNPC and SIGKDD paper DRM.
  ☆85Updated 11 months ago
• Hhhhhhao / General-Framework-Weak-Supervision
  This repo provides the codebase for "A General Framework for Weak Supervision"
  ☆34Updated 10 months ago
• Vanint / Core-tuning
  This repository is the official implementation of Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regulari…
  ☆21Updated 2 years ago
• Hhhhhhao / Noisy-Model-Learning
  ☆35Updated last year
• Lifelong-ML / LASEM
  Code for the ICML 2021 paper "Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer Transfer"
  ☆11Updated 3 years ago
• songweige / Contrastive-Learning-with-Non-Semantic-Negatives
  Robust Contrastive Learning Using Negative Samples with Diminished Semantics (NeurIPS 2021)
  ☆38Updated 3 years ago
• mjy1111 / PEAK
  The repository for our paper: Neighboring Perturbations of Knowledge Editing on Large Language Models
  ☆16Updated 10 months ago
• salesforce / ensemble-of-averages
  ☆29Updated last year
• LFhase / PAIR
  [ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization
  ☆52Updated 11 months ago
• yaohungt / Self_Supervised_Learning_Multiview
  ☆42Updated 4 years ago
• huaxiuyao / LISA
  LISA for ICML 2022
  ☆47Updated last year
• lancopku / well-classified-examples-are-underestimated
  Code for the AAAI 2022 publication "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"
  ☆51Updated 2 years ago
• youjiangxu / FaMUS
  ☆28Updated 3 years ago
• bhanML / SIGUA
  ICML'20: SIGUA: Forgetting May Make Learning with Noisy Labels More Robust
  ☆15Updated 4 years ago
• wyf0912 / MIXALL
  [ICASSP 2020] Code release of paper 'Heterogeneous Domain Generalization via Domain Mixup'
  ☆25Updated 4 years ago
• sooonwoo / CL-Baselines
  This is a Pytorch implementation of contrastive Learning(CL) baselines.
  ☆13Updated 2 years ago
• ShuheSH / A-Survey-of-the-Reasoning-Abilities-of-LLMs
  ☆19Updated 3 weeks ago
• tmllab / 2021_NeurIPS_PES
  ☆29Updated 2 years ago
• AlanChou / Super-Loss
  PyTorch implementation of the paper "SuperLoss: A Generic Loss for Robust Curriculum Learning" in NIPS 2020.
  ☆30Updated 4 years ago