cywinski / guideLinks
☆13Updated last year
Alternatives and similar repositories for guide
Users that are interested in guide are comparing it to the libraries listed below
Sorting:
- [CVPR2024] Efficient Dataset Distillation via Minimax Diffusion☆104Updated last year
- Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality (NeurIPS 2023, Spotlight)☆90Updated last year
- source code for NeurIPS'23 paper "Dream the Impossible: Outlier Imagination with Diffusion Models"☆72Updated 9 months ago
- [CVPR2024 highlight] Generalized Large-Scale Data Condensation via Various Backbone and Statistical Matching (G-VBSM)☆28Updated last year
- [NeurIPS 2024, spotlight] Scaling Out-of-Distribution Detection for Multiple Modalities☆68Updated last month
- Code for ICML2023 paper, DDGR: Continual Learning with Deep Diffusion-based Generative Replay.☆39Updated 2 years ago
- Official implementation of "Mixture of Experts Meets Prompt-Based Continual Learning" (NeurIPS 2024)☆40Updated 5 months ago
- Code for ICML 2024 paper (Oral) — Test-Time Model Adaptation with Only Forward Passes☆92Updated last year
- Awesome list of Mixture-of-Experts (MoE)☆26Updated last year
- Everything to the Synthetic: Diffusion-driven Test-time Adaptation via Synthetic-Domain Alignment, arXiv 2024 / CVPR 2025☆39Updated 10 months ago
- Awesome Low-Rank Adaptation☆59Updated 5 months ago
- ☆16Updated last year
- Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need (IJCV 2024)☆153Updated last year
- This is the official PyTorch Implementation of "SoTTA: Robust Test-Time Adaptation on Noisy Data Streams (NeurIPS '23)" by Taesik Gong*, …☆23Updated last year
- Consistent Prompting for Rehearsal-Free Continual Learning [CVPR2024]☆36Updated 7 months ago
- PyTorch implementation of various distillation approaches for continual learning of Diffusion Models.☆26Updated 10 months ago
- A paper list of our recent survey on continual learning, and other useful resources in this field.☆101Updated last year
- Efficient Dataset Distillation by Representative Matching☆113Updated last year
- PyTorch code for the CVPR'23 paper: "CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual Learning"☆156Updated 2 years ago
- Practical Continual Forgetting for Pre-trained Vision Models (CVPR 2024; T-PAMI 2026)☆70Updated 2 weeks ago
- A pytorch implementation of CVPR24 paper "D4M: Dataset Distillation via Disentangled Diffusion Model"☆37Updated last year
- [NeurIPS '24] Frustratingly easy Test-Time Adaptation of VLMs!!☆60Updated 10 months ago
- [CVPR'25 (Highlight)] Lessons and Insights from a Unifying Study of Parameter-Efficient Fine-Tuning (PEFT) in Visual Recognition☆46Updated 7 months ago
- Awsome of VLM-CL. Continual Learning for VLMs: A Survey and Taxonomy Beyond Forgetting☆145Updated last week
- Official implementation for CVPR'23 paper "BlackVIP: Black-Box Visual Prompting for Robust Transfer Learning"☆109Updated 2 years ago
- The official implementation of the CVPR'2024 work Interference-Free Low-Rank Adaptation for Continual Learning☆102Updated 10 months ago
- [ICLR 2024] ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation☆71Updated last year
- ✌ CLoG: Benchmarking Continual Learning of Image Generation Models☆20Updated last year
- Code for paper "Boosting Continual Learning of Vision-Language Models via Mixture-of-Experts Adapters" CVPR2024☆269Updated 4 months ago
- Instruction Tuning in Continual Learning paradigm☆71Updated 11 months ago