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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/jathurshan0330/cross-modal-transformer

공식 코드

Toward Interpretable Sleep Stage Classification Using Cross-Modal Transformers

https://github.com/javierorjuela/bayesian-neural-net-with-mnfs-for-f-r-

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Bayesian deep learning for cosmic volumes with modified gravity

https://github.com/jaylago/dldmd

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Deep Learning Enhanced Dynamic Mode Decomposition

https://github.com/jbartlett6/sdnet

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Recovering high-quality FODs from a reduced number of diffusion-weighted images using a model-driven deep learning architecture

https://github.com/jbayrooti/dp-dec-learning

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Generalizing Differentially Private Decentralized Deep Learning with Multi-Agent Consensus

https://github.com/jbramburger/Deep-Conjugacies

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Deep Learning of Conjugate Mappings

https://github.com/jeffheaton/t81_558_deep_learning

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Applications of Deep Neural Networks with Keras

https://github.com/jeremy-chopin/apacosi

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Model-based inexact graph matching on top of CNNs for semantic scene understanding

https://github.com/jeshraghian/snntorch

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Training Spiking Neural Networks Using Lessons From Deep Learning

https://github.com/jess-jpg-txt/dae_for_adv_attacks_in_mimo

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Defending Adversarial Attacks on Deep Learning Based Power Allocation in Massive MIMO Using Denoising Autoencoders

https://github.com/jesus-333/Dynamic-PyTorch-Net

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CNN-based Approaches For Cross-Subject Classification in Motor Imagery: From The State-of-The-Art to DynamicNet

https://github.com/jesus-333/FBCSP-Python

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CNN-based Approaches For Cross-Subject Classification in Motor Imagery: From The State-of-The-Art to DynamicNet

https://github.com/jianf-wang/gbdl

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Rethinking Bayesian Deep Learning Methods for Semi-Supervised Volumetric Medical Image Segmentation

https://github.com/jiangmeng-jm/cognitive-pathways---deep-learning

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AI-Enhanced Cognitive Behavioral Therapy: Deep Learning and Large Language Models for Extracting Cognitive Pathways from Social Media Texts

https://github.com/jiangyuan2li/deep-spatio-temporal

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Deep Spatio-Temporal Wind Power Forecasting

https://github.com/jiaqingxie/deepprotein

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DeepProtein: Deep Learning Library and Benchmark for Protein Sequence Learning

https://github.com/jiarunliu/co-correcting

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Co-Correcting: Noise-tolerant Medical Image Classification via mutual Label Correction

https://github.com/jiashunwang/MRT

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Adversarial Attention for Human Motion Synthesis

https://github.com/jieli12/autocpd

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Automatic Change-Point Detection in Time Series via Deep Learning

https://github.com/jiesutd/yato

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YATO: Yet Another deep learning based Text analysis Open toolkit

https://github.com/jimengshi/dl-foundation-models-weather

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Deep Learning and Foundation Models for Weather Prediction: A Survey

https://github.com/jimengshi/dl-walef

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Deep Learning Models for Flood Predictions in South Florida

https://github.com/jimengshi/fidlar

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FIDLAR: Forecast-Informed Deep Learning Architecture for Flood Mitigation

https://github.com/jimgammell/gan_side_channel_leakage_detector

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Power side-channel leakage localization through adversarial training of deep neural networks

https://github.com/jin-smile/improved-related-key-differential-based-neural-distinguishers

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Improved (Related-key) Differential-based Neural Distinguishers for SIMON and SIMECK Block Ciphers

https://github.com/jingfeng-lu/deep-ultrafast-echocardiography

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Ultrafast Cardiac Imaging Using Deep Learning For Speckle-Tracking Echocardiography

https://github.com/jinhokim46/mrcp_dlrecon

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Deep Learning-based Accelerated MR Cholangiopancreatography without Fully-sampled Data

https://github.com/jinshanzeng/admm-deeplearning

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On ADMM in Deep Learning: Convergence and Saturation-Avoidance

https://github.com/jinshuaibai/pgdl_review

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Utilising physics-guided deep learning to overcome data scarcity

https://github.com/jinxhy/smartappattack

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Smart App Attack: Hacking Deep Learning Models in Android Apps

https://github.com/jjdabr/forecastNet

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ForecastNet: A Time-Variant Deep Feed-Forward Neural Network Architecture for Multi-Step-Ahead Time-Series Forecasting

https://github.com/jklj077/meProp

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meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting

https://github.com/jmaces/aapm-ct-challenge

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Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning

https://github.com/jmaces/robust-nets

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Solving Inverse Problems With Deep Neural Networks -- Robustness Included?

https://github.com/jmcardenas/cas4dl

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CAS4DL: Christoffel Adaptive Sampling for function approximation via Deep Learning

https://github.com/jmdvinodjmd/HyperITE

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A Brief Review of Hypernetworks in Deep Learning

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