https://github.com/dr-bell/kaizen
공식 코드Kaizen: Practical Self-supervised Continual Learning with Continual Fine-tuning
Papers with Code 아카이브
Knowledge Distillation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
- 11
- 보존된 평가 기록
- 90
Knowledge distillation is the process of transferring knowledge from a large model to a smaller one. While large models (such as very deep neural networks or ensembles of many models) have higher knowledge capacity than small models, this capacity might not be fully utilized.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/dragon-wu/depcov-www2023
공식 코드Exploring Social Media for Early Detection of Depression in COVID-19 Patients
https://github.com/dreamguo/UNIKD
공식 코드UNIKD: UNcertainty-filtered Incremental Knowledge Distillation for Neural Implicit Representation
https://github.com/dreamtheater123/voxeval
공식 코드VoxEval: Benchmarking the Knowledge Understanding Capabilities of End-to-End Spoken Language Models
https://github.com/drilistbox/CWD
공식 코드https://github.com/drorlab/glow_ives
공식 코드https://github.com/drsleep/nas-segm-pytorch
공식 코드Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells
https://github.com/dshi3553usyd/frameless_graph_distillation
공식 코드https://github.com/dssg/aequitas
공식 코드https://github.com/dtennant/mirb_eval
공식 코드https://github.com/ducha-aiki/navigation-benchmark
공식 코드Benchmarking Classic and Learned Navigation in Complex 3D Environments
https://github.com/dudwns511/dcd_cikm21
공식 코드Dual Correction Strategy for Ranking Distillation in Top-N Recommender System
https://github.com/duggalrahul/MICCAI17_EndoVis_RoboSeg
공식 코드https://github.com/duguodong7/graftllm
공식 코드https://github.com/dunnkers/msc-thesis
공식 코드A novel evaluation methodology for supervised Feature Ranking algorithms
https://github.com/duongpm/SPSO
공식 코드Safety-enhanced UAV Path Planning with Spherical Vector-based Particle Swarm Optimization
https://github.com/durgas16/AMAL
공식 코드https://github.com/duyngtr16061999/kdmcse
공식 코드https://github.com/duzhixing/FRS
공식 코드https://github.com/dvlab-research/dsig
공식 코드Deep Structured Instance Graph for Distilling Object Detectors
https://github.com/dvlab-research/msad
공식 코드Multi-Scale Aligned Distillation for Low-Resolution Detection
https://github.com/dwang181/active-mixup
공식 코드https://github.com/dwzhu-pku/longembed
공식 코드LongEmbed: Extending Embedding Models for Long Context Retrieval
https://github.com/dxli94/WLASL
공식 코드https://github.com/dyahayumgw/HAAQI-Net
공식 코드HAAQI-Net: A Non-intrusive Neural Music Audio Quality Assessment Model for Hearing Aids
https://github.com/dyoony/srst_awr
공식 코드https://github.com/dzcgaara/OVO
공식 코드https://github.com/dzy3/kcd
공식 코드https://github.com/e-tornike/sil
공식 코드https://github.com/eason-li-ais/drafterbench
공식 코드DrafterBench: Benchmarking Large Language Models for Tasks Automation in Civil Engineering
https://github.com/ebagdasa/federated_adaptation
공식 코드https://github.com/ebalti/Low-Complexity-Hybrid-Beamforming-For-MmWave-Full-Duplex-Integrated-Access-And-Backhaul
공식 코드Low Complexity Hybrid Beamforming for mmWave Full-Duplex Integrated Access and Backhaul
https://github.com/ebtisaamcs/rkd
공식 코드Robust Knowledge Distillation in Federated Learning: Counteracting Backdoor Attacks
https://github.com/eccv2024mse/eccv_mse_teacher
공식 코드How to Train the Teacher Model for Effective Knowledge Distillation
https://github.com/eceo-epfl/coralscapesScripts
공식 코드The Coralscapes Dataset: Semantic Scene Understanding in Coral Reefs
https://github.com/ecker-lab/object-centric-representation-benchmark
공식 코드Benchmarking Unsupervised Object Representations for Video Sequences
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.