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Specificity

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

https://github.com/christiantinauer/binADNI

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Pfungst and Clever Hans: Identifying the unintended cues in a widely used Alzheimer's disease MRI dataset using explainable deep learning

https://github.com/chtmp223/topicgpt

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TopicGPT: A Prompt-based Topic Modeling Framework

https://github.com/chunmeifeng/fedmri

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Specificity-Preserving Federated Learning for MR Image Reconstruction

https://github.com/ci-ber/thor_ddpm

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Diffusion Models with Implicit Guidance for Medical Anomaly Detection

https://github.com/cic4k/NERC_ChatGPT

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Yes but.. Can ChatGPT Identify Entities in Historical Documents?

https://github.com/clementchadebec/benchmark_VAE

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Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder

https://github.com/clementchadebec/pyraug

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Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder

https://github.com/clickff/adseqgan

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Auxiliary Discrminator Sequence Generative Adversarial Networks (ADSeqGAN) for Few Sample Molecule Generation

https://github.com/cltl/DutchDescriptions

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Cross-linguistic differences and similarities in image descriptions

https://github.com/cmaldonado1/predicting-cvd-using-oct-images

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Predicting risk of cardiovascular disease using retinal OCT imaging

https://github.com/cnnlstm/stylegan_matting

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Self-supervised Matting-specific Portrait Enhancement and Generation

https://github.com/codermillat/StudyAbroadGPT

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A LoRA-Based Approach to Fine-Tuning LLMs for Educational Guidance in Resource-Constrained Settings

https://github.com/codesfornlp/ttea

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Type-enhanced Ensemble Triple Representation via Triple-aware Attention for Cross-lingual Entity Alignment

https://github.com/congboma/disentanglesum

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Disentangling Specificity for Abstractive Multi-document Summarization

https://github.com/controlagent/controlagent

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ControlAgent: Automating Control System Design via Novel Integration of LLM Agents and Domain Expertise

https://github.com/coughresearch/Cough-signal-processing

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Pay Attention to the cough: Early Diagnosis of COVID-19 using Interpretable Symptoms Embeddings with Cough Sound Signal Processing

https://github.com/cricketclub/gridspace-stanford-harper-valley

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HarperValleyBank: A Domain-Specific Spoken Dialog Corpus

https://github.com/csinva/imodels

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Fast Interpretable Greedy-Tree Sums

https://github.com/cvangysel/cuNVSM

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Neural Vector Spaces for Unsupervised Information Retrieval

https://github.com/cviviers/3D_UNetSecondaryFeatures

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Improved Pancreatic Tumor Detection by Utilizing Clinically-Relevant Secondary Features

https://github.com/czi-ai/oc-guidance

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Variational Control for Guidance in Diffusion Models

https://github.com/darwinai/TuberculosisNet

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TB-Net: A Tailored, Self-Attention Deep Convolutional Neural Network Design for Detection of Tuberculosis Cases from Chest X-ray Images

https://github.com/david26694/sktools

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Quantile Encoder: Tackling High Cardinality Categorical Features in Regression Problems

https://github.com/davidecolla/semantic_coherence_markers

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Semantic Coherence Markers for the Early Diagnosis of the Alzheimer Disease

https://github.com/deepcar/taillight_recognition

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Nighttime Driver Behavior Prediction Using Taillight Signal Recognition via CNN-SVM Classifier

https://github.com/deepinmotion/shapgcn

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Explaining Human Activity Recognition with SHAP: Validating Insights with Perturbation and Quantitative Measures

https://github.com/demolakstate/eGAN_addressing_class_imbalance_with_transfer_learning_on_GAN

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eGAN: Unsupervised approach to class imbalance using transfer learning

https://github.com/deskk/AbGPT

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AbGPT: De Novo Antibody Design via Generative Language Modeling

https://github.com/difanj0713/spin

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SPIN: Sparsifying and Integrating Internal Neurons in Large Language Models for Text Classification

https://github.com/digital-ecmt/llm_factuality_evaluation_framework

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Large Language Models, scientific knowledge and factuality: A framework to streamline human expert evaluation

https://github.com/dingchenyang99/pensieve

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Pensieve: Retrospect-then-Compare Mitigates Visual Hallucination

https://github.com/diponkor-bala/autism-spectrum-disorder

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An Evaluation of Machine Learning Approaches for Early Diagnosis of Autism Spectrum Disorder

https://github.com/docbrisky/coronary-occlusion

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Augmenting expert detection of early coronary artery occlusion from 12 lead electrocardiograms using deep learning

https://github.com/doerlbh/topologicalrsa

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The Topology and Geometry of Neural Representations

https://github.com/dong03/MVSS-Net

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Image Manipulation Detection by Multi-View Multi-Scale Supervision

https://github.com/dpetrini/two-views-classifier

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Breast Cancer Diagnosis in Two-View Mammography Using End-to-End Trained EfficientNet-Based Convolutional Network

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.