Alternatives and similar repositories for LCMat

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

• sdh0818 / FreD
  Official PyTorch implementation for Frequency Domain-based Dataset Distillation [NeurIPS 2023]
  ☆30Updated last year
• yaolu-zjut / DDInterpreter
  ☆15Updated last year
• Saehyung-Lee / DCC
  This repository is the official implementation of Dataset Condensation with Contrastive Signals (DCC), accepted at ICML 2022.
  ☆22Updated 3 years ago
• VICO-UoE / IT-GAN
  ☆23Updated 2 years ago
• uitrbn / IDM
  ☆27Updated 2 years ago
• princetonvisualai / RememberThePast-DatasetDistillation
  ☆39Updated 2 years ago
• deeplearning-wisc / dice
  Code for ECCV 2022 paper "DICE: Leveraging Sparsification for Out-of-Distribution Detection"
  ☆40Updated 3 years ago
• zzzx1224 / EBTSA-ICLR2023
  ☆11Updated 8 months ago
• snu-mllab / Efficient-Dataset-Condensation
  Official PyTorch implementation of "Dataset Condensation via Efficient Synthetic-Data Parameterization" (ICML'22)
  ☆113Updated 2 years ago
• AngusDujw / FTD-distillation
  The code of the paper "Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation" (CVPR2023)
  ☆40Updated 2 years ago
• justincui03 / dc_benchmark
  ☆87Updated 2 years 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…
  ☆46Updated 3 years ago
• pandeydeep9 / EvidentialResearch2023
  Analysis of evidential models
  ☆14Updated 2 years ago
• ZFancy / Unleashing-Mask
  [ICML 2023] "Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability"
  ☆18Updated 2 years ago
• OPTML-Group / DP4TL
  [NeurIPS2023] "Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning" by Yihua Zhang*, Yimeng Zhang*,…
  ☆14Updated 2 years ago
• QizhouWang / DOE
  ☆26Updated 2 years ago
• yu-rp / Distribution-Shift-Iverson
  ☆41Updated 2 years ago
• dengbaowang / Mixup-Inference-in-Training
  This is the implementation of our CVPR'23 paper On the Pitfall of Mixup for Uncertainty Calibration. In the paper, we conduct a series of…
  ☆17Updated 2 years ago
• Kthyeon / FINE_official
  NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"
  ☆40Updated 3 years ago
• locuslab / tta_conjugate
  Test-Time Adaptation via Conjugate Pseudo-Labels
  ☆42Updated 2 years ago
• LijieFan / AdvCL
  [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”
  ☆48Updated 3 years ago
• zhangmarvin / memo
  ☆68Updated 2 years ago
• kakaoenterprise / Learning-Debiased-Disentangled
  Official Pytorch implementation of "Learning Debiased Representation via Disentangled Feature Augmentation (Neurips 2021, Oral)"
  ☆104Updated 2 years ago
• he-y / Multisize-Dataset-Condensation
  Official PyTorch implementation of "Multisize Dataset Condensation" (ICLR'24 Oral)
  ☆15Updated last year
• abonte / protopdebug
  Implementation of Concept-level Debugging of Part-Prototype Networks
  ☆12Updated 2 years ago
• deeplearning-wisc / gradnorm_ood
  On the Importance of Gradients for Detecting Distributional Shifts in the Wild
  ☆56Updated 3 years ago
• tfzhou / FedFA
  ICLR 2023 - FedFA: Federated Feature Augmentation
  ☆59Updated 2 years ago
• naver-ai / cmo
  ☆48Updated 2 years ago
• DataDistillation / DataDAM
  [ICCV 2023] DataDAM: Efficient Dataset Distillation with Attention Matching
  ☆34Updated last year
• dhanajitb / petal
  Probabilistic lifElong Test-time Adaptation with seLf-training prior (PETAL)
  ☆13Updated 2 years ago