Top Tweets for #InterpretableMachineLearning
🔔 New Published Papers of #MDPIfutureinternet
Title: Explaining Seasonal 5G Path Loss in a Vineyard: From Empirical Models to #InterpretableMachineLearning
https://t.co/hUGXi49v0s
#5Gcommunications; path loss prediction; RSRP measurement; glass-box model; NDVI; smart farming
【🎉Latest accepted article】
#Trajectory of Vegetation Productivity and Drivers of Abrupt Changes Following Afforestation in the #SouthChinaKarst
#VegetationDynamics | #XGBoost_SHAP | #InterpretableMachineLearning
@MaximumAcademic
https://t.co/wlkeKKQhJa
Google’s pwlfit distills ML models into simple, human-readable curve code, matching black-box accuracy. - https://t.co/i4TP7VadUI #interpretablemachinelearning #googlepwlfitlibrary
🥰Welcome to read👉"An #InterpretableMachineLearning Approach to Predict #SensoryProcessingSensitivityTrait in #NursingStudents"🗒️by🧑🏫Dr. A. Ponce-Valencia et al.:🧷https://t.co/oGv19LaeRl
#sensoryprocessingsensitivity #emotionalintelligence #conflictresolution #machinelearning
If you are attending IJCAI2025, consider attending my talk at the XAI Workshop!
#interpretablemachinelearning #ijcai2025 #ijcai25 #IJCAI2025XAI #IJCAI25XAI #IJCAI25_Workshops #XAIworkshop25 #ExperienceDrexel #drexel #drexeluniversity #drexelcci #drexelcciresearch #drexelproud
📢 Read our Review Paper
📚 Making Sense of Machine Learning: A Review of Interpretation Techniques and Their Applications
🔗 https://t.co/Bb3J5mk24b
👨🔬 by Ainura Tursunalieva et al.
#interpretablemachinelearning #interpretationtechniques
🏥 This study focuses on the use of #interpretablemachinelearning to #predict unscheduled #hospitalreadmissions, which contribute significantly to healthcare costs, particularly for chronic patients.
👉 https://t.co/smtg3IyH4o
New study by Sugie Lee et al aims to investigate the nonlinear relationships and threshold effects between #CrimePatterns and street-level neighbourhood environments using #MachineLearning models and the #InterpretableMachineLearning technique
https://t.co/CXcqaOqdg6
@hippdude1
🔥 Read our Highly Cited Paper
📚 Explainable Machine Learning for Lung Cancer Screening Models
🔗 https://t.co/TfFE9jlpa3
👨🔬 by Mrs. Katarzyna Kobylińska et al.
#interpretablemachinelearning
@UniWarszawski
#mdpienergies #highlycitedpaper
#Review on #InterpretableMachineLearning in #SmartGrid
👉 https://t.co/cIgqStoOxv
#explainableartificialintelligence #deeplearning
Machine Learning Unveils Strategies for Enhanced Flood Mitigation
#AI #artificialintelligence #Climate #communitylevelpolicies #empoweringvulnerablegroups #floodinsurance #floodingcosts #highresidentturnover #interpretablemachinelearning #llm
https://t.co/iuSFvGPabm
Thanks to Parul Verma , Malhar Patel, MD and Sanjay Ghosh for their amazing talks, this was an exciting 3rd edition of the Special Session XAIB @BrainInformatics2023 Stevens Institute of Technology, Hoboken, NY #explainableartificialintelligence #interpretablemachinelearning
🎉 Just joined Twitter! Excited to share my 1st tweet: SOTAI's no-code #InterpretableML platform, Artifice. Harness shape constraints & calibrated models in any industry! 🚀
👉 https://t.co/F3m7cldf7X
#MachineLearning #AI #XAI #InterpretableAI #InterpretableMachineLearning
#highlycitedpaper
A Clinically Interpretable Computer-Vision Based Method for Quantifying Gait in #Parkinson’s Disease
https://t.co/gvKx51BkI1
#gait #timeseriesanalysis #computervision #poseestimation #interpretablemachinelearning
@ucl
@UofCalifornia
@USouthFlorida
#NewArticle
Categorizing Shallow #MarineSoundscapes Using Explained Clusters https://t.co/QzlnmHNvIT #mdpijmse via @JMSE_MDPI
@ResearchUGent
@FondationUQO
#ecoacoustics #interpretablemachinelearning #RandomForest #shallowwater #SHAP #UMAP #XAI
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