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

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

공식 코드

Globally Scalable Glacier Mapping by Deep Learning Matches Expert Delineation Accuracy

https://github.com/koushik-n/Active-Learning-Plant-Phenotyping

공식 코드

How useful is Active Learning for Image-based Plant Phenotyping?

https://github.com/kqwang/DLPR

공식 코드

Deep learning phase recovery: data-driven, physics-driven, or combining both?

https://github.com/kqwang/phase-recovery

공식 코드

On the use of deep learning for phase recovery

https://github.com/kreimanlab/DeepLearning-vs-HighLevelVision

공식 코드

Can Deep Learning Recognize Subtle Human Activities?

https://github.com/kuangdai/sofa

공식 코드

Deep Learning Evidence for Global Optimality of Gerver's Sofa

https://github.com/kungfu-team/tenplex

공식 코드

Tenplex: Dynamic Parallelism for Deep Learning using Parallelizable Tensor Collections

https://github.com/kunqi1994/deep-learning-on-rail-profile-matching

공식 코드

Deep learning on rail profiles matching

https://github.com/l-bg/categorical_perception_ann_neco

공식 코드

Categorical Perception: A Groundwork for Deep Learning

https://github.com/lab-smile/domino

공식 코드

DOMINO: Domain-aware Loss for Deep Learning Calibration

https://github.com/lamtung16/ML_ChangepointDetection

공식 코드

Enhancing Changepoint Detection: Penalty Learning through Deep Learning Techniques

https://github.com/lancopku/meProp

공식 코드

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

https://github.com/larajuse/DMAE

공식 코드

Dissimilarity Mixture Autoencoder for Deep Clustering

https://github.com/larsonlab/dnlinv

공식 코드

Scan-specific Self-supervised Bayesian Deep Non-linear Inversion for Undersampled MRI Reconstruction

https://github.com/lasandrall/ideepviewlearn

공식 코드

Interpretable Deep Learning Methods for Multiview Learning

https://github.com/lasigeBioTM/BiONT

공식 코드

BiOnt: Deep Learning using Multiple Biomedical Ontologies for Relation Extraction

https://github.com/laura-rieger/deep-explanation-penalization

공식 코드

Interpretations are useful: penalizing explanations to align neural networks with prior knowledge

https://github.com/laurencee9/structural_pertubation_detection

공식 코드

Detecting structural perturbations from time series with deep learning

https://github.com/lbai-lab/push

공식 코드

Push: Concurrent Probabilistic Programming for Bayesian Deep Learning

https://github.com/lbnlcomputerarch/graphene-u-net

공식 코드

Deep Learning Segmentation of Complex Features in Atomic-Resolution Phase Contrast Transmission Electron Microscopy Images

https://github.com/lcmd-epfl/equireact

공식 코드

3DReact: Geometric deep learning for chemical reactions

https://github.com/le-trungnguyen/neurips2024-activationcompression

공식 코드

Activation Map Compression through Tensor Decomposition for Deep Learning

https://github.com/learning-at-home/hivemind

공식 코드

Distributed Deep Learning in Open Collaborations

https://github.com/learningkeqi/rethinkingbca

공식 코드

Rethinking Functional Brain Connectome Analysis: Do Graph Deep Learning Models Help?

https://github.com/learningmatter-mit/NeuralForceField

공식 코드

Molecular machine learning with conformer ensembles

https://github.com/lebrat/MongeNet

공식 코드

MongeNet: Efficient Sampler for Geometric Deep Learning

https://github.com/leixuai/hyperspectral

공식 코드

Dropout Concrete Autoencoder for Band Selection on HSI Scenes

https://github.com/leixuai/imbalanced_crack_detection_with_gans

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Revisiting Generative Adversarial Networks for Binary Semantic Segmentation on Imbalanced Datasets

https://github.com/lelouedec/phd_3dperception

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3D shape sensing and deep learning-based segmentation of strawberries

https://github.com/lennartjaretzki/geometricdeeplearningknotdata

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Geometric deep learning approach to knot theory

https://github.com/leon-bit-9527/ener

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E-NER: Evidential Deep Learning for Trustworthy Named Entity Recognition

https://github.com/leon022/edgepro

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Edge Deep Learning Model Protection via Neuron Authorization

https://github.com/leonty1/spatiotemporal-observer

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Spatiotemporal Observer Design for Predictive Learning of High-Dimensional Data

https://github.com/lessw2020/Ranger21

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Ranger21: a synergistic deep learning optimizer

https://github.com/libingyu01/qitsa-quantum-inspired-interpretable-deep-learning-architecture-for-text-sentiment-analysis

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Quantum-inspired Interpretable Deep Learning Architecture for Text Sentiment Analysis

https://github.com/lich0031/AIDE

공식 코드

Annotation-efficient deep learning for automatic medical image segmentation

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