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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/mskcc-computational-pathology/dmmn-ovary

공식 코드

Deep Interactive Learning-based ovarian cancer segmentation of H&E-stained whole slide images to study morphological patterns of BRCA mutation

https://github.com/msuzen/research/tree/main/gibbs-randomness-compression

공식 코드

Gibbs randomness-compression proposition: An efficient deep learning

https://github.com/mtrager/polynomial_networks

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On the Expressive Power of Deep Polynomial Neural Networks

https://github.com/muqiaoy/dl_signal

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Complex Transformer: A Framework for Modeling Complex-Valued Sequence

https://github.com/muqiaoy/egemaps_estimator

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Improving Speech Enhancement through Fine-Grained Speech Characteristics

https://github.com/mwalmsley/zoobot

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A Comparison of Deep Learning Architectures for Optical Galaxy Morphology Classification

https://github.com/mwalmsley/zoobot-3d

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Deep Learning Segmentation of Spiral Arms and Bars

https://github.com/mynotwo/a-fast-transformer-based-general-purpose-losslesscompressor

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A Fast Transformer-based General-Purpose Lossless Compressor

https://github.com/mystic-blue/collective-learning

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An effective theory of collective deep learning

https://github.com/naamiinepal/smartphone_microscopy

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Deep-learning Assisted Detection and Quantification of (oo)cysts of Giardia and Cryptosporidium on Smartphone Microscopy Images

https://github.com/nadeemlab/CEP

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RT-GAN: Recurrent Temporal GAN for Adding Lightweight Temporal Consistency to Frame-Based Domain Translation Approaches

https://github.com/nadeemlab/Physics-ArX

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RMSim: Controlled Respiratory Motion Simulation on Static Patient Scans

https://github.com/nadeemlab/seqx2y

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RMSim: Controlled Respiratory Motion Simulation on Static Patient Scans

https://github.com/nar-k/NIPS-2018

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Step Size Matters in Deep Learning

https://github.com/navidfoumani/tsc_survey

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Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey

https://github.com/ncbi-nlp/DeepSeeNet

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A deep learning approach for automated detection of geographic atrophy from color fundus photographs

https://github.com/ncclabsustech/EEGdenoiseNet

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EEGdenoiseNet: A benchmark dataset for end-to-end deep learning solutions of EEG denoising

https://github.com/ncclabsustech/Single-Channel-EEG-Denoise

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EEGdenoiseNet: A benchmark dataset for end-to-end deep learning solutions of EEG denoising

https://github.com/ncfrey/litmatter

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Scalable Geometric Deep Learning on Molecular Graphs

https://github.com/ndraeger/waba

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Backdoor Attacks for Remote Sensing Data with Wavelet Transform

https://github.com/ndrwmlnk/stroke-rendering

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Stroke-based Rendering: From Heuristics to Deep Learning

https://github.com/neeharperi/PreferenceNet

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PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning

https://github.com/nemo9cby/icse2022rep

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Towards Training Reproducible Deep Learning Models

https://github.com/nengo/nengo-dl

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NengoDL: Combining deep learning and neuromorphic modelling methods

https://github.com/neopenx/Dragon

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Dragon: A Computation Graph Virtual Machine Based Deep Learning Framework

https://github.com/nestordemeure/flaxoptimizers

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Ranger21: a synergistic deep learning optimizer

https://github.com/netrias/DOODL3

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Extracting Global Dynamics of Loss Landscape in Deep Learning Models

https://github.com/neuraldl/dlatypicalserotoninergiccells

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Deep Learning Models for Atypical Serotonergic Cells Recognition

https://github.com/neuralml/burstccn

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Single-phase deep learning in cortico-cortical networks

https://github.com/neuroevobench/neuroevobench

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NeuroEvoBench: Benchmarking Evolutionary Optimizers for Deep Learning Applications

https://github.com/neurospin-projects/2022_lguillon_rare_folding_detection

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Identification of Rare Cortical Folding Patterns using Unsupervised Deep Learning

https://github.com/ngessert/4d_deep_learning

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Deep learning with 4D spatio-temporal data representations for OCT-based force estimation

https://github.com/ngk03/dir-dist-loss

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Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint

https://github.com/ngk03/dl_ppg_review

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A Review of Deep Learning Methods for Photoplethysmography Data

https://github.com/nguwijy/deep_branching

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A deep branching solver for fully nonlinear partial differential equations

https://github.com/nh2tran/DeepNovo

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Protein identification with deep learning: from abc to xyz

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