Papers with Code 아카이브
Data-free Knowledge Distillation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 2
- 보존된 평가 기록
- 8
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/gregoirepetit/echodfkd
공식 코드EchoDFKD: Data-Free Knowledge Distillation for Cardiac Ultrasound Segmentation using Synthetic Data
https://github.com/gregor-ge/foci-benchmark
공식 코드https://github.com/gsig/actions-for-actions
공식 코드What Actions are Needed for Understanding Human Actions in Videos?
https://github.com/gsisaoki/omnidirectional_blender_3d_dataset
공식 코드OB3D: A New Dataset for Benchmarking Omnidirectional 3D Reconstruction Using Blender
https://github.com/gsk-ai/leak-proof-cmap
공식 코드https://github.com/gt-salt/mic
공식 코드The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systems
https://github.com/gt-star-lab/jaxrobotarium
공식 코드JaxRobotarium: Training and Deploying Multi-Robot Policies in 10 Minutes
https://github.com/gtDMMB/pmfe2023
공식 코드Can geometric combinatorics improve RNA branching predictions?
https://github.com/gtfintechlab/worldcentralbanks
공식 코드Words That Unite The World: A Unified Framework for Deciphering Central Bank Communications Globally
https://github.com/gtfintechlab/zero-shot-finance
공식 코드Zero is Not Hero Yet: Benchmarking Zero-Shot Performance of LLMs for Financial Tasks
https://github.com/gtzheng/fewstab
공식 코드https://github.com/gugarosa/opf_distance
공식 코드Comparative Study Between Distance Measures On Supervised Optimum-Path Forest Classification
https://github.com/guiliang/cirl-benchmarks-public
공식 코드Benchmarking Constraint Inference in Inverse Reinforcement Learning
https://github.com/guiliang/icrl-benchmarks-public
공식 코드Benchmarking Constraint Inference in Inverse Reinforcement Learning
https://github.com/gulnazaki/counterfactual-benchmark
공식 코드https://github.com/guoleisun/indiscernible-object-counting
공식 코드https://github.com/gusye1234/recad
공식 코드RecAD: Towards A Unified Library for Recommender Attack and Defense
https://github.com/gyhou123/egosocialarena
공식 코드https://github.com/gykovacs/retina_vessel_segmentation
공식 코드https://github.com/h-jamieu/noisy_ostracods
공식 코드https://github.com/hahamyt/mst
공식 코드MST: Adaptive Multi-Scale Tokens Guided Interactive Segmentation
https://github.com/haihabi/learned-bcrb
공식 코드Learned Bayesian Cramér-Rao Bound for Unknown Measurement Models Using Score Neural Networks
https://github.com/haileyfamo/insqabench
공식 코드InsQABench: Benchmarking Chinese Insurance Domain Question Answering with Large Language Models
https://github.com/haksorus/gsplatloc
공식 코드https://github.com/hakuhodo-technologies/scope-rl
공식 코드Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation
https://github.com/hamedhematian/importantnews
공식 코드KhabarChin: Automatic Detection of Important News in the Persian Language
https://github.com/hanjiechen/challengeclinicalqa
공식 코드Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questions
https://github.com/hanjuku-kaso/awesome-offline-rl
공식 코드CORL: Research-oriented Deep Offline Reinforcement Learning Library
https://github.com/hannafoe/cryptanalytical-extraction
공식 코드https://github.com/hannahblo/23_performance_analysis_ml_algorithms
공식 코드Depth Functions for Partial Orders with a Descriptive Analysis of Machine Learning Algorithms
https://github.com/hannahblo/comparing_algorithms_using_ufg_depth
공식 코드Comparing Machine Learning Algorithms by Union-Free Generic Depth
https://github.com/hannahblo/posets_optimizers
공식 코드https://github.com/hannahblo/statistical_multicriteria_evaluation_of_llm-generated_text
공식 코드https://github.com/hanniewhu/remm
공식 코드REMM:Rotation-Equivariant Framework for End-to-End Multimodal Image Matching
https://github.com/hanyue1648/reft
공식 코드Reference Twice: A Simple and Unified Baseline for Few-Shot Instance Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.