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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/sccn/deep-channel-harmonization

공식 코드

Deep learning applied to EEG data with different montages using spatial attention

https://github.com/scfischer/dirk-et-al-2022

공식 코드

Recognition and reconstruction of cell differentiation patterns with deep learning

https://github.com/schnarc/schnarc

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Combining SchNet and SHARC: The SchNarc machine learning approach for excited-state dynamics

https://github.com/schufo/umss

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Unsupervised Music Source Separation Using Differentiable Parametric Source Models

https://github.com/scientific-computing-lab-nrcn/multi-view-foams

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Determining HEDP Foams' Quality with Multi-View Deep Learning Classification

https://github.com/scientific-computing/FKB

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A Fortran-Keras Deep Learning Bridge for Scientific Computing

https://github.com/scverse/scvi-tools

공식 코드

Deep Learning in Single-Cell Analysis

https://github.com/sdfk72auga1kwsi/aalf

공식 코드

AALF: Almost Always Linear Forecasting

https://github.com/sdittmer/survival_analysis_sumo_plus_plus

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Reinterpreting survival analysis in the universal approximator age

https://github.com/seanjparker/rlflow

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RLFlow: Optimising Neural Network Subgraph Transformation with World Models

https://github.com/seanywang0408/rasf

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Representation-Agnostic Shape Fields

https://github.com/sebchw/actually-robust-training

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ART: Actually Robust Training

https://github.com/secondmind-labs/GPflux

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GPflux: A Library for Deep Gaussian Processes

https://github.com/sehwankimstat/SCENE

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Self-Consistent Equation-guided Neural Networks for Censored Time-to-Event Data

https://github.com/senli1073/seist

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SeisT: A foundational deep learning model for earthquake monitoring tasks

https://github.com/seominseok0429/w4c22-simple-baseline-for-weather-forecasting-using-spatiotemporal-context-aggregation-network

공식 코드

Simple Baseline for Weather Forecasting Using Spatiotemporal Context Aggregation Network

https://github.com/seon82/musedetect

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A Hierarchical Deep Learning Approach for Minority Instrument Detection

https://github.com/sergeyprokudin/deep_direct_stat

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Deep Directional Statistics: Pose Estimation with Uncertainty Quantification

https://github.com/serval-uni-lu/tabularbench

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TabularBench: Benchmarking Adversarial Robustness for Tabular Deep Learning in Real-world Use-cases

https://github.com/set-path/multi-input-mushroom-recognition

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Taxonomy and evolution predicting using deep learning in images

https://github.com/sfc-computational-creativity-lab/RhythmVAE_M4L

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Towards democratizing music production with AI-Design of Variational Autoencoder-based Rhythm Generator as a DAW plugin

https://github.com/sfc-computational-creativity-lab/x-rhythm-can

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Can GAN originate new electronic dance music genres? -- Generating novel rhythm patterns using GAN with Genre Ambiguity Loss

https://github.com/sftekin/ieee_weather

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Numerical Weather Forecasting using Convolutional-LSTM with Attention and Context Matcher Mechanisms

https://github.com/sfu-mial/skin-lesion-segmentation-survey

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A Survey on Deep Learning for Skin Lesion Segmentation

https://github.com/sgfin/adversarial-medicine

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Adversarial Attacks Against Medical Deep Learning Systems

https://github.com/sh-src/automf

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Automated Fusion of Multimodal Electronic Health Records for Better Medical Predictions

https://github.com/shafiq-islam-cse/multimodal-marvels-of-deep-learning-using-image-speech-and-text-review-of-covid-19-detection

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Multimodal Marvels of Deep Learning in Medical Diagnosis: A Comprehensive Review of COVID-19 Detection

https://github.com/shahroztariq/CLRNet

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One Detector to Rule Them All: Towards a General Deepfake Attack Detection Framework

https://github.com/shakedshammah/failures_of_DL

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Failures of Gradient-Based Deep Learning

https://github.com/shamanDevel/IsosurfaceSuperresolution

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Volumetric Isosurface Rendering with Deep Learning-Based Super-Resolution

https://github.com/shanay-mehta/anomaly-benchmarking

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Can Tree Based Approaches Surpass Deep Learning in Anomaly Detection? A Benchmarking Study

https://github.com/sharathadavanne/doa-net

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Differentiable Tracking-Based Training of Deep Learning Sound Source Localizers

https://github.com/sharathadavanne/hungarian-net

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Differentiable Tracking-Based Training of Deep Learning Sound Source Localizers

https://github.com/sharpiless/nanocrystals-deep-learning

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Deep Learning Models for Colloidal Nanocrystal Synthesis

https://github.com/sharpiless/nanocrystals-tem-segmentation

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Deep Learning Models for Colloidal Nanocrystal Synthesis

https://github.com/shauqi/ss-cvae

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Semi-Supervised Contrastive VAE for Disentanglement of Digital Pathology Images

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