Oliver-FutureAI / Awesome-MoELinks
Awesome list of Mixture-of-Experts (MoE)
☆21Updated last year
Alternatives and similar repositories for Awesome-MoE
Users that are interested in Awesome-MoE are comparing it to the libraries listed below
Sorting:
- [CVPR2024] Efficient Dataset Distillation via Minimax Diffusion☆96Updated last year
- A pytorch implementation of CVPR24 paper "D4M: Dataset Distillation via Disentangled Diffusion Model"☆35Updated 11 months ago
- Code for our ICML'24 on multimodal dataset distillation☆38Updated 10 months ago
- [CVPR 2024] On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm☆73Updated 6 months ago
- [ICML 2023] On Pitfalls of Test-Time Adaptation☆120Updated last year
- ☆29Updated 2 years ago
- [NeurIPS'23] DropPos: Pre-Training Vision Transformers by Reconstructing Dropped Positions☆61Updated last year
- The official implementation of "2024NeurIPS Dynamic Tuning Towards Parameter and Inference Efficiency for ViT Adaptation"☆46Updated 8 months ago
- [TPAMI 2024] Probabilistic Contrastive Learning for Long-Tailed Visual Recognition☆82Updated 11 months ago
- Code for ICML 2024 paper (Oral) — Test-Time Model Adaptation with Only Forward Passes☆85Updated last year
- Efficient Dataset Distillation by Representative Matching☆112Updated last year
- [CVPR2024 highlight] Generalized Large-Scale Data Condensation via Various Backbone and Statistical Matching (G-VBSM)☆28Updated 10 months ago
- Code for ICLR 2023 paper (Oral) — Towards Stable Test-Time Adaptation in Dynamic Wild World☆191Updated last year
- ICLR 2024, Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching☆101Updated last year
- Official implementation for 'Class-Balancing Diffusion Models'☆54Updated last year
- Official implementation for CVPR'23 paper "BlackVIP: Black-Box Visual Prompting for Robust Transfer Learning"☆111Updated 2 years ago
- Distilling Dataset into Generative Models☆54Updated 2 years ago
- The official github repo for "Test-Time Training with Masked Autoencoders"☆88Updated last year
- [ICLR 2025 Oral🔥] SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning☆55Updated 2 months ago
- ☆113Updated last year
- (NeurIPS 2023 spotlight) Large-scale Dataset Distillation/Condensation, 50 IPC (Images Per Class) achieves the highest 60.8% on original …☆129Updated 9 months ago
- [ICLR 2024 (Spotlight)] "Frozen Transformers in Language Models are Effective Visual Encoder Layers"☆242Updated last year
- Code for ICML2023 paper, DDGR: Continual Learning with Deep Diffusion-based Generative Replay.☆38Updated 2 years ago
- Code for ICML 2022 paper — Efficient Test-Time Model Adaptation without Forgetting☆128Updated 2 years ago
- ☆16Updated last year
- [NeurIPS 2024, spotlight] Scaling Out-of-Distribution Detection for Multiple Modalities☆64Updated 3 months ago
- Official repository of "Back to Source: Diffusion-Driven Test-Time Adaptation"☆80Updated last year
- [ICCV 2023] A Unified Continual Learning Framework with General Parameter-Efficient Tuning☆88Updated 10 months ago
- [NeurIPS'24 Oral] HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning☆222Updated 9 months ago
- Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality (NeurIPS 2023, Spotlight)☆87Updated 9 months ago