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Knowledge Distillation

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하위 태스크: 2
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/chenxiliu-hnu/cm2ts

Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillation

https://github.com/chenyang4/resmooth

Circumventing Outliers of AutoAugment with Knowledge Distillation

https://github.com/chenzhenpeng18/biasmitigationstudy

AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

https://github.com/chenzhenpeng18/fse22-maat

AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

https://github.com/chenzhenpeng18/icse24-multi-attribute-fairness

AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

https://github.com/chenzhenpeng18/tosem23-biasmitigationstudy

AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

https://github.com/chicagohai/hypothesis-generation

HypoBench: Towards Systematic and Principled Benchmarking for Hypothesis Generation

https://github.com/chicagohai/hypothesis_generation

HypoBench: Towards Systematic and Principled Benchmarking for Hypothesis Generation

https://github.com/chloroExtractorTeam/benchmark

Essential guidelines for computational method benchmarking

https://github.com/chr26195/pmlp

Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks

https://github.com/chrispsa/lamp_benchmark

Benchmarking the Linear Algebra Awareness of TensorFlow and PyTorch

https://github.com/chriswegmann/drone_steering

Learning Deep and Compact Models for Gesture Recognition

https://github.com/chrysts/geodesic_continual_learning

On Learning the Geodesic Path for Incremental Learning

https://github.com/chunhuililili/mt_dnn

Improving Multi-Task Deep Neural Networks via Knowledge Distillation for Natural Language Understanding

https://github.com/cleverhans-lab/cleverhans

Technical Report on the CleverHans v2.1.0 Adversarial Examples Library

https://github.com/clip-italian/clip-italian

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/clip-vil/cider

CIDEr: Consensus-based Image Description Evaluation

https://github.com/cloudnine148/PHC_2nd_SPC

Focal Loss for Dense Object Detection

https://github.com/coMindOrg/federated-averaging-tutorials

Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

https://github.com/code-implementation1/Code2/tree/main/AlphaPose

AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time

https://github.com/code-implementation1/Code4/tree/main/lite-hrnet

HRNET: AI on Edge for mask detection and social distancing

https://github.com/coendevente/nninteractive-slicer

nnInteractive: Redefining 3D Promptable Segmentation

https://github.com/coldsummerday/mmdetection-zhou

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/comp-well-org/Data_Augmentation_for_Biobehavioral_Time_Series_Data

Role of Data Augmentation Strategies in Knowledge Distillation for Wearable Sensor Data

https://github.com/conda-forge/r-biglasso-feedstock

The biglasso Package: A Memory- and Computation-Efficient Solver for Lasso Model Fitting with Big Data in R

https://github.com/congvm-it/pyciderevalcap

CIDEr: Consensus-based Image Description Evaluation

https://github.com/cooldawnant/infochartqa

ChartGalaxy: A Dataset for Infographic Chart Understanding and Generation

https://github.com/coperception/coperception

Learning Distilled Collaboration Graph for Multi-Agent Perception

https://github.com/coqui-ai/TTS

FastSpeech 2: Fast and High-Quality End-to-End Text to Speech

https://github.com/cornell-zhang/dnn-gating

Channel Gating Neural Networks

https://github.com/coronazap/bert_client

Well-Read Students Learn Better: On the Importance of Pre-training Compact Models

https://github.com/cospplay/bert-master

Well-Read Students Learn Better: On the Importance of Pre-training Compact Models

https://github.com/courros/hnco

COCO: Performance Assessment

https://github.com/csm-kr/Retinanet_pytorch

Focal Loss for Dense Object Detection

https://github.com/csuzhuzhuxia/GlassDetect

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/ctuning/artifact-evaluation

Enabling more efficient and cost-effective AI/ML systems with Collective Mind, virtualized MLOps, MLPerf, Collective Knowledge Playground and reproducible optimization tournaments

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.