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

https://github.com/jmj2316/KARINA

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KARINA: An Efficient Deep Learning Model for Global Weather Forecast

https://github.com/jmjmalik22/hate-speech-detection

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Deep Learning for Hate Speech Detection: A Comparative Study

https://github.com/joaoantoniocn/AM-MobileNet1D

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AM-MobileNet1D: A Portable Model for Speaker Recognition

https://github.com/joaoantoniocn/AM-SincNet

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Additive Margin SincNet for Speaker Recognition

https://github.com/johannesulf/nautilus

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NAUTILUS: boosting Bayesian importance nested sampling with deep learning

https://github.com/johncolddd/ppn

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A Physics-Inspired Deep Learning Framework with Polar Coordinate Attention for Ptychographic Imaging

https://github.com/johnnellas/csae

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Supervised Dimensionality Reduction and Image Classification Utilizing Convolutional Autoencoders

https://github.com/johnnyzn/MalRNN

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Binary Black-box Evasion Attacks Against Deep Learning-based Static Malware Detectors with Adversarial Byte-Level Language Model

https://github.com/johnwlambert/dlupi-heteroscedastic-dropout

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Deep Learning under Privileged Information Using Heteroscedastic Dropout

https://github.com/jokeryan/post_training

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Adaptive Modeling Against Adversarial Attacks

https://github.com/jonasw247/a-learnable-prior-improves-inverse-tumor-growth-modeling

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A Learnable Prior Improves Inverse Tumor Growth Modeling

https://github.com/jonathanwider/DLWP-eval-extremes

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Validating Deep Learning Weather Forecast Models on Recent High-Impact Extreme Events

https://github.com/jordan-g/segregated-dendrite-deep-learning

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Towards deep learning with segregated dendrites

https://github.com/joshuachou2018/afs

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Audit to Forget: A Unified Method to Revoke Patients' Private Data in Intelligent Healthcare

https://github.com/josiahwsmith10/Radar-Musical-Instrument

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An FCNN-Based Super-Resolution mmWave Radar Framework for Contactless Musical Instrument Interface

https://github.com/josiahwsmith10/josiahwsmith10

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Novel Hybrid-Learning Algorithms for Improved Millimeter-Wave Imaging Systems

https://github.com/jpeginspireddl/jpeg-inspired-dl

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JPEG Inspired Deep Learning

https://github.com/jrg2223/utilising-deep-learning-to-elicit-expert-uncertainty

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Utilising Deep Learning to Elicit Expert Uncertainty

https://github.com/js05212/BayesianDeepLearning-Survey

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A Survey on Bayesian Deep Learning

https://github.com/ju-resplande/dlb_absapt2022

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Deep Learning Brasil at ABSAPT 2022: Portuguese Transformer Ensemble Approaches

https://github.com/juditacs/deep-morphology

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The Role of Interpretable Patterns in Deep Learning for Morphology

https://github.com/juliagraphs/graphneuralnetworks.jl

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GraphNeuralNetworks.jl: Deep Learning on Graphs with Julia

https://github.com/juliameister/dl-confident-loss-function

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A novel Deep Learning approach for one-step Conformal Prediction approximation

https://github.com/julieeF/CS231N-Project

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Emotion Recognition in Audio and Video Using Deep Neural Networks

https://github.com/juliusberner/robust_kolmogorov

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Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning

https://github.com/junjun-jiang/Face-Hallucination-Benchmark

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Deep Learning-based Face Super-Resolution: A Survey

https://github.com/junzengz/cirrhosisstage

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Liver Cirrhosis Stage Estimation from MRI with Deep Learning

https://github.com/juselara1/dmae

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Dissimilarity Mixture Autoencoder for Deep Clustering

https://github.com/jvhs0706/zkdl-train

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zkDL: Efficient Zero-Knowledge Proofs of Deep Learning Training

https://github.com/jwwthu/DL4Stock

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Applications of deep learning in stock market prediction: recent progress

https://github.com/jwwthu/GNN-Communication-Networks

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Graph-based Deep Learning for Communication Networks: A Survey

https://github.com/jwyyy/AdaFNN

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Deep Learning for Functional Data Analysis with Adaptive Basis Layers

https://github.com/jxbz/agd

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Automatic Gradient Descent: Deep Learning without Hyperparameters

https://github.com/kaidic/HAR

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Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization

https://github.com/kailasdayanandan/dual_thinking

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Dual Thinking and Logical Processing -- Are Multi-modal Large Language Models Closing the Gap with Human Vision ?

https://github.com/kaleidophon/experimental-standards-deep-learning-research

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Experimental Standards for Deep Learning in Natural Language Processing Research

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