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

https://github.com/DanyWind/fastai_bs_finder

An Empirical Model of Large-Batch Training

https://github.com/DeNeutoy/Decomposable_Attn

A Decomposable Attention Model for Natural Language Inference

https://github.com/Deci-AI/super-gradients

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/DeepBrainsMe/FSnet

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/DeepSceneSeg/SSMA

Self-Supervised Model Adaptation for Multimodal Semantic Segmentation

https://github.com/Deskaunedsei1983/jukebox-openai

Jukebox: A Generative Model for Music

https://github.com/DevonFulcher/CryptoPricePredictor

WaveNet: A Generative Model for Raw Audio

https://github.com/Devwalkar/BOC-KD

Online Ensemble Model Compression using Knowledge Distillation

https://github.com/DigitalPhonetics/reading-comprehension

A Compare-Aggregate Model for Matching Text Sequences

https://github.com/Driesssens/ibp-pytorch

Learning model-based planning from scratch

https://github.com/Eom-taeseon/CV_SceneTextRecognition

What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis

https://github.com/Epoch-Mengying/Generating-Poetry-with-Chatbot

A Multi-Modal Chinese Poetry Generation Model

https://github.com/EugenHotaj/pytorch-generative/blob/master/pytorch_generative/models/autoregressive/pixel_snail.py

PixelSNAIL: An Improved Autoregressive Generative Model

https://github.com/Faceplugin-ltd/FaceLivenessDetection-Android

An Ensemble Model for Face Liveness Detection

https://github.com/FuxiCV/pt_mesh_renderer

Unsupervised Training for 3D Morphable Model Regression

https://github.com/GAMES-UChile/mogptk

SAMBA: Safe Model-Based & Active Reinforcement Learning

https://github.com/GISH123/Cathay-Holdings-CIP-Projects-for-Interpretable-Machine-Learning

A Unified Approach to Interpreting Model Predictions

https://github.com/Gal1eo/DT2119

WaveNet: A Generative Model for Raw Audio

https://github.com/Ganeshpadmanaban/Neural-Attention-Model

A Neural Attention Model for Abstractive Sentence Summarization

https://github.com/Ganeshpadmanaban/Neural-Attention-Model-Abstractive-Summarization

A Neural Attention Model for Abstractive Sentence Summarization

https://github.com/Gourhari/README

NeVAE: A Deep Generative Model for Molecular Graphs

https://github.com/HCPLab-SYSU/SR

Dual-Glance Model for Deciphering Social Relationships

https://github.com/HO4X/TSR_JetsonTX2

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/HaiFengZeng/clari_wavenet_vocoder

WaveNet: A Generative Model for Raw Audio

https://github.com/HectorHHZ/Sparse_Matrix_Tuning

Sparse Matrix in Large Language Model Fine-tuning

https://github.com/Hermina/GLMM

Graph Laplacian mixture model

https://github.com/Hmkhalla/NLP-summarizer

A Deep Reinforced Model for Abstractive Summarization

https://github.com/HongshengHu/SIAs-Beyond_MIAs_in_Federated_Learning

FedMD: Heterogenous Federated Learning via Model Distillation

https://github.com/HsiehKang/wavenet/blob/main/wavenet.ipynb

WaveNet: A Generative Model for Raw Audio

https://github.com/HyeonhoonLee/MAIC2021_Sleep

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/IBCNServices/skMAPLE

Model Agnostic Supervised Local Explanations

https://github.com/IBM/vsrl-framework

Verifiably Safe Off-Model Reinforcement Learning

https://github.com/IBM/wasserstein-barycenters

Wasserstein Barycenter Model Ensembling

https://github.com/ICB-DCM/model_calibration_protocol

A protocol for dynamic model calibration

https://github.com/IMvision12/keras-vision-models

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/IanWangg/NeurlPS-Reproduce-Chanllenge

Fooling Neural Network Interpretations via Adversarial Model Manipulation

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