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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/jxbz/modula

Modular Duality in Deep Learning

https://github.com/jzyee/cms_image_classification

Application of a Convolutional Neural Network for image classification to the analysis of collisions in High Energy Physics

https://github.com/kage08/qmdp-net

QMDP-Net: Deep Learning for Planning under Partial Observability

https://github.com/kaist-silab/graphsplinenets

Learning Efficient Surrogate Dynamic Models with Graph Spline Networks

https://github.com/kaleidophon/nlp-uncertainty-zoo

A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness

https://github.com/kalelpark/DeepLearning-for-Tabular-Data

Revisiting Deep Learning Models for Tabular Data

https://github.com/kamata1729/QATM_pytorch

QATM: Quality-Aware Template Matching For Deep Learning

https://github.com/kampta/pytorch-distributions

TensorFlow Distributions

https://github.com/karakusc/horovod

Horovod: fast and easy distributed deep learning in TensorFlow

https://github.com/karanwxliaa/CapSecure

Vulnerability analysis of captcha using Deep learning

https://github.com/karnwatcharasupat/DeepNewsvendor

Applying Deep Learning to the Newsvendor Problem

https://github.com/kartikey-singh/Replicating-SeER

SeER: An Explainable Deep Learning MIDI-based Hybrid Song Recommender System

https://github.com/keonlee9420/DailyTalk

Exploring Transfer Learning for Low Resource Emotional TTS

https://github.com/keonlee9420/Expressive-FastSpeech2

Exploring Transfer Learning for Low Resource Emotional TTS

https://github.com/kesslerlib/kessler

Towards Automated Satellite Conjunction Management with Bayesian Deep Learning

https://github.com/keunwoochoi/dl4mir

A Tutorial on Deep Learning for Music Information Retrieval

https://github.com/keyuchen886/GoodReads

Wide & Deep Learning for Recommender Systems

https://github.com/khaamosh/Deep-Learning-Japanese-Character-Recognition

Deep Learning for Classical Japanese Literature

https://github.com/khatria/Retrieving-Similar-E-Commerce-Images-Using-Deep-Learning

Retrieving Similar E-Commerce Images Using Deep Learning

https://github.com/khieu/cifar10_challenge

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/klarh/geometric_algebra_attention

Geometric Algebra Attention Networks for Small Point Clouds

https://github.com/klemens-floege/svn_ensembles

Laplace Redux -- Effortless Bayesian Deep Learning

https://github.com/klimzaporojets/DWIE

Deep Joint Entity Disambiguation with Local Neural Attention

https://github.com/klin059/lits

Automated Design of Deep Learning Methods for Biomedical Image Segmentation

https://github.com/kolbrak/Modulation_Classification

Over the Air Deep Learning Based Radio Signal Classification

https://github.com/konstantin-a-maslov/towards_global_glacier_mapping

Globally Scalable Glacier Mapping by Deep Learning Matches Expert Delineation Accuracy

https://github.com/kousun12/TFDE

Solving high-dimensional partial differential equations using deep learning

https://github.com/krantirk/The-Fortran-Keras-Bridge-FKB-

A Fortran-Keras Deep Learning Bridge for Scientific Computing

https://github.com/krishnakarthi/COVID-19_Prediction

Xception: Deep Learning with Depthwise Separable Convolutions

https://github.com/kupuSs/DIEN-pipline

Deep Interest Evolution Network for Click-Through Rate Prediction

https://github.com/kwotsin/TensorFlow-Xception

Xception: Deep Learning with Depthwise Separable Convolutions

https://github.com/kyeongsoo/indoor_localization

Low-effort place recognition with WiFi fingerprints using deep learning

https://github.com/kyle-dorman/bayesian-neural-network-blogpost

What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?

https://github.com/kylemath/DeepEEG

Deep learning-based electroencephalography analysis: a systematic review

https://github.com/kyleolsz/public-kaolin

Kaolin: A PyTorch Library for Accelerating 3D Deep Learning Research

https://github.com/kzkadc/poly-nets

$Π-$nets: Deep Polynomial Neural Networks

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