Papers with Code 아카이브

model

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

0

보존된 평가 기록

0

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/yaroslav-moiseev/evidence-based-possibly-best-practices-in-classical-ML

A Unified Approach to Interpreting Model Predictions

https://github.com/ydc123/Meta_Surrogate_Model

Training Meta-Surrogate Model for Transferable Adversarial Attack

https://github.com/yebiny/DepthOfAnaesthesia_eeg

WaveNet: A Generative Model for Raw Audio

https://github.com/yiboyang/otus

Sliced-Wasserstein Autoencoder: An Embarrassingly Simple Generative Model

https://github.com/yifan-song793/eto

Direct Preference Optimization: Your Language Model is Secretly a Reward Model

https://github.com/yihaosun1124/OfflineRL-Kit

MOPO: Model-based Offline Policy Optimization

https://github.com/yixinwang/vbmisspec-public

Variational Bayes under Model Misspecification

https://github.com/yjlee22/cyclicaggregation

Model-Contrastive Federated Learning

https://github.com/yoojungsun0/Psych239

Model-Free Episodic Control

https://github.com/youngwoo-yoon/Practical-tips-for-lightweight-deep-learning

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/yramon/ShapCounterfactual

A Unified Approach to Interpreting Model Predictions

https://github.com/ysbsb/ReXNet-PyTorch

Rethinking Channel Dimensions for Efficient Model Design

https://github.com/ysoullard/CTCModel

CTCModel: a Keras Model for Connectionist Temporal Classification

https://github.com/yuchenxia/aasbyllm

LLM experiments with simulation: Large Language Model Multi-Agent System for Simulation Model Parametrization in Digital Twins

https://github.com/yuhengsss/msvmamba

VMamba: Visual State Space Model

https://github.com/yuzhimanhua/HIMECat

On a Model for Integrated Information

https://github.com/yyimingucl/dgp

Linked Deep Gaussian Process Emulation for Model Networks

https://github.com/zejiangh/Filter-GaP

CHEX: CHannel EXploration for CNN Model Compression

https://github.com/zejiangh/Multi-dimensional-vit-compression

Multi-Dimensional Model Compression of Vision Transformer

https://github.com/zhaoolee/garss

TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters

https://github.com/zhaoyi11/tcrl

Temporal Difference Learning for Model Predictive Control

https://github.com/zhaozixiang1228/mmif-cddfuse

Image Fusion via Vision-Language Model

https://github.com/zhaozixiang1228/mmif-emma

Image Fusion via Vision-Language Model

https://github.com/zhengli97/promptkd

Cascade Prompt Learning for Vision-Language Model Adaptation

https://github.com/zhiyuan-zeng/evaltree

QualEval: Qualitative Evaluation for Model Improvement

https://github.com/zhong110020/Tensorflow-TCN

WaveNet: A Generative Model for Raw Audio

https://github.com/zhong110020/keras-tcn

WaveNet: A Generative Model for Raw Audio

https://github.com/zhongpeixiang/ckc

Keyword-Guided Neural Conversational Model

https://github.com/ziangcao0312/DiffTF

Large-Vocabulary 3D Diffusion Model with Transformer

https://github.com/zju-vipa/KamalEngine

Deep Model Transferability from Attribution Maps

https://github.com/zju-vipa/cmi

Contrastive Model Inversion for Data-Free Knowledge Distillation

https://github.com/zjunlp/deepke

Reasoning with Language Model Prompting: A Survey

https://github.com/zll1996/TCN

WaveNet: A Generative Model for Raw Audio

https://github.com/zs1314/microscopic-mamba

VMamba: Visual State Space Model

https://github.com/zs1314/octamamba

VMamba: Visual State Space Model

https://github.com/zs1314/skinmamba

VMamba: Visual State Space Model

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