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Deep Learning

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

https://github.com/theidentity/Improved-GAN-PyTorch

Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images

https://github.com/theswgong/MoNet

Geometric deep learning on graphs and manifolds using mixture model CNNs

https://github.com/theycallmepeter/pytorch3d_PBR

Accelerating 3D Deep Learning with PyTorch3D

https://github.com/thibaultvt/Diard

LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis

https://github.com/thinklab-sjtu/linsatnet

Deep Learning for Portfolio Optimization

https://github.com/thisiskhan/tensorflow-developer-certificate-machine-learning-kit

A guide to convolution arithmetic for deep learning

https://github.com/thlarsen13/thlarsen_uncertainty_models

Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning

https://github.com/thomashopkins32/PGDAdversarialLearning

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/thouyang/ccd-dsa

Guiding Deep Learning System Testing using Surprise Adequacy

https://github.com/thunil/Deep-Flow-Prediction

Physics-based Deep Learning

https://github.com/thunlp/ReInfoSelect

TU Wien @ TREC Deep Learning '19 -- Simple Contextualization for Re-ranking

https://github.com/tianhai123/-

Tensor2Tensor for Neural Machine Translation

https://github.com/tianzheng4/Distributionally-Adversarial-Attack

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/tianzhou2011/FiLM

FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting

https://github.com/tigthor/neural-network-hacking

Hacking Neural Networks: A Short Introduction

https://github.com/timeseriesAI/tsai/blob/main/tsai/models/GatedTabTransformer.py

The GatedTabTransformer. An enhanced deep learning architecture for tabular modeling

https://github.com/timeseriesAI/tsai/blob/main/tsai/models/InceptionTime.py

InceptionTime: Finding AlexNet for Time Series Classification

https://github.com/timeseriesAI/tsai/blob/main/tsai/models/mWDN.py

Multilevel Wavelet Decomposition Network for Interpretable Time Series Analysis

https://github.com/timeseriesAI/tsai/tree/main/tsai/models

Self-attention for raw optical Satellite Time Series Classification

https://github.com/tlacombe/topt

A Topology Layer for Machine Learning

https://github.com/tmulc18/Distributed-TensorFlow-Guide

Deep learning with Elastic Averaging SGD

https://github.com/tomerraviv95/bayesian-learning-in-receivers-for-decoding

Learning to Decode Linear Codes Using Deep Learning

https://github.com/tomerraviv95/metadeepsic

ViterbiNet: A Deep Learning Based Viterbi Algorithm for Symbol Detection

https://github.com/tommasopuccetti/adversarial_perturbation

MagNet: a Two-Pronged Defense against Adversarial Examples

https://github.com/tongzheng1992/Pavementscapes

Pavementscapes: a large-scale hierarchical image dataset for asphalt pavement damage segmentation

https://github.com/tonybeltramelli/Deep-Spying

Deep-Spying: Spying using Smartwatch and Deep Learning

https://github.com/torchjd/torchjd

Multi-objective Deep Learning: Taxonomy and Survey of the State of the Art

https://github.com/tpsatish95/indus-script-ocr

Deep Learning the Indus Script

https://github.com/trungson077/beauty_eva

SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception

https://github.com/trupewate/lung_segmentation_tutorial

Towards Robust Lung Segmentation in Chest Radiographs with Deep Learning

https://github.com/trusthlt/dp-nmt

Deep Learning with Differential Privacy

https://github.com/trusthlt/granularity-is-crucial-dp

Deep Learning with Differential Privacy

https://github.com/tud-ccc/compy-learn

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis

https://github.com/tufts-ml/bdl-transfer-learning

Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors

https://github.com/twitter-research/tgn

Temporal Graph Networks for Deep Learning on Dynamic Graphs

https://github.com/tychen5/sportslottery

DeepSign: Deep Learning for Automatic Malware Signature Generation and Classification

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