Papers with Code 아카이브

Sensitivity

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

0

보존된 평가 기록

0

코드

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

https://github.com/rdlin118/hilots

공식 코드

HiLoTs: High-Low Temporal Sensitive Representation Learning for Semi-Supervised LiDAR Segmentation in Autonomous Driving

https://github.com/reaile/bias-explainer

공식 코드

How Biased are Your Features?: Computing Fairness Influence Functions with Global Sensitivity Analysis

https://github.com/redwankarimsony/weightperturbation-msu

공식 코드

Investigating Weight-Perturbed Deep Neural Networks With Application in Iris Presentation Attack Detection

https://github.com/rem-h4/llm_socialbias_prompts

공식 코드

Social Bias Evaluation for Large Language Models Requires Prompt Variations

https://github.com/retailmarketingai/retailsynth

공식 코드

RetailSynth: Synthetic Data Generation for Retail AI Systems Evaluation

https://github.com/richardobi/medigan

공식 코드

High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection

https://github.com/rlgraph/rlgraph

공식 코드

RLgraph: Modular Computation Graphs for Deep Reinforcement Learning

https://github.com/rmastand/nsbi_for_dihiggs

공식 코드

Constraining the Higgs Potential with Neural Simulation-based Inference for Di-Higgs Production

https://github.com/saba96/img-cap-metrics-robustness

공식 코드

An Examination of the Robustness of Reference-Free Image Captioning Evaluation Metrics

https://github.com/sahilsethi0105/scope-mri

공식 코드

Toward Non-Invasive Diagnosis of Bankart Lesions with Deep Learning

https://github.com/sambklein/dequantile

공식 코드

Decorrelation with conditional normalizing flows

https://github.com/samleoqh/viola-unet

공식 코드

Examining Deployment and Refinement of the VIOLA-AI Intracranial Hemorrhage Model Using an Interactive NeoMedSys Platform

https://github.com/samwilso/safe_official

공식 코드

SAFE: Sensitivity-Aware Features for Out-of-Distribution Object Detection

https://github.com/sangheek16/dialogue-response-dynamics

공식 코드

"No, they did not": Dialogue response dynamics in pre-trained language models

https://github.com/satwik77/transformer-simplicity

공식 코드

Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions

https://github.com/sdv4/Predicting-Confusion-with-RNN_HAI-2019

공식 코드

Predicting Confusion from Eye-Tracking Data with Recurrent Neural Networks

https://github.com/serhatadik/opengert

공식 코드

OpenGERT: Open Source Automated Geometry Extraction with Geometric and Electromagnetic Sensitivity Analyses for Ray-Tracing Propagation Models

https://github.com/serizba/cliquemining

공식 코드

Close, But Not There: Boosting Geographic Distance Sensitivity in Visual Place Recognition

https://github.com/shayanalipour/llm-alignment-bias

공식 코드

Robustness and Confounders in the Demographic Alignment of LLMs with Human Perceptions of Offensiveness

https://github.com/shikiw/si-adv

공식 코드

Shape-invariant 3D Adversarial Point Clouds

https://github.com/shiyuchengtju/par

공식 코드

Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal

https://github.com/shreyahavaldar/multicultural_emotion

공식 코드

Multilingual Language Models are not Multicultural: A Case Study in Emotion

https://github.com/shu-hai/SA_DNN

공식 코드

Sensitivity Analysis of Deep Neural Networks

https://github.com/simi912/deep-convolutional-neural-network-classifier-for-alzheimer-s-disease-1

공식 코드

SNeurodCNN: Structure-focused Neurodegeneration Convolutional Neural Network for Modelling and Classification of Alzheimer's Disease

https://github.com/simone-bombari/attention-sensitivity

공식 코드

Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features

https://github.com/sinanyildirim/smc_dp_adatr

공식 코드

Differentially Private Online Bayesian Estimation With Adaptive Truncation

https://github.com/skp1999/SMAB

공식 코드

SMAB: MAB based word Sensitivity Estimation Framework and its Applications in Adversarial Text Generation

https://github.com/sleighsoft/fti

공식 코드

Improving the Evaluation of Generative Models with Fuzzy Logic

https://github.com/slimgroup/Software.SEG2020

공식 코드

Uncertainty quantification in imaging and automatic horizon tracking: a Bayesian deep-prior based approach

https://github.com/smg478/OralCancerDetectionOnCTImages

공식 코드

Computer Aided Detection of Oral Lesions on CT Images

https://github.com/smoothken/kknet

공식 코드

Towards Improving Harmonic Sensitivity and Prediction Stability for Singing Melody Extraction

https://github.com/smstrzd/IntegratedGradCAM

공식 코드

Integrated Grad-CAM: Sensitivity-Aware Visual Explanation of Deep Convolutional Networks via Integrated Gradient-Based Scoring

https://github.com/sobalgi/rhognf

공식 코드

$ρ$-GNF: A Copula-based Sensitivity Analysis to Unobserved Confounding Using Normalizing Flows

https://github.com/socialfoundations/benchbench

공식 코드

Inherent Trade-Offs between Diversity and Stability in Multi-Task Benchmarks

https://github.com/srebuffi/revisiting_saliency

공식 코드

There and Back Again: Revisiting Backpropagation Saliency Methods

https://github.com/sriramb-98/blindspots-neurips-sub

공식 코드

Exploring Geometry of Blind Spots in Vision Models

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