Top Tweets for #interpretableML
It clearly explains common pitfalls with interpretability tools like SHAP, saliency maps, and feature attribution, and how to apply them more responsibly in real biological workflows.
#InterpretableML #ExplainableAI #AIinBiology #DataScience #MLinBiology #NatureMethods #Science
#EGU26 has officially started in Vienna 🇦🇹
If you're working on #Deep_Learning , #InterpretableML , or environmental ML, I'm 📍 at EGU all week. Coffee chats welcome :)
🗓 Presenting Wed 6 May, 15:15 CEST, Room B, Session HS 🔗
https://t.co/LJsB76rUx0
Arian presenting our work on measuring the #uncertainty of visual #explanations from autonomous navigation systems at the #ACRAI research day.
A paper with more details is in the works. A link will follow soon.
#InterpretableML #XAI #AI #ML #UAI #sqIRL #IDLab #UAntwerp #imec
[2603.00496] A Polynomial-Time Axiomatic Alternative to SHAP for Feature Attribution
#MachineLearning #ExplainableAI #XAI #SHAP #InterpretableML #GameTheory #CooperativeGameTheory #FeatureAttribution #AIResearch #DataScience #arXiv https://t.co/I6hpRL7ajt
📣#CallforPapers!
☑️Efficient #DeepLearning Models and Applications
🗓️ Deadline: 15 June 2026
🔗More Info: https://t.co/686sWjpxib
Guest Editors from Scuola Superiore Sant’Anna
#DL #AI #ML #NLP #LLM #GNN #ReservoirComputing
#InterpretableML #QuantumComputing #bioinformatics
Explainable AI: The push for AI systems to provide transparent reasoning for their decisions, boosting trust and accountability. #ExplainableAI #Transparency #TrustworthyAI #EthicalAI #InterpretableML #AIdaily #AItrend #ArtificialIntelligence
This week our lab was present at the Flanders AI Research day. There we contributed with a deep dive session on #Compositional #Interpretability.
More details at: https://t.co/CrRJL61hnB
#CompInterp #interpretableML #XAI #explainability #aisafety #ML #AI
📢 Paper Alert!
A comprehensive review of how fuzzy logic enhances interpretability & explainability in ML across domains like healthcare, energy & finance.
🔗 https://t.co/P9WgK9LR4t
#ExplainableAI #FuzzyLogic #InterpretableML #TrustworthyAI #PhDChat #AcademicTwitter
Paper: https://t.co/aTgXPh9pHU
Code: https://t.co/OsN05DNA9a
#InterpretableML #AIinCancer #SingleCell #MultiOmics #InterpretableAI #CancerGenomics #OpenScience #Bioinformatics #ComputationalBiology #MachineLearning
74% of companies can’t scale AI.
Not because it’s inaccurate, because it’s incomprehensible.
The future? Predictive systems that explain themselves.
Read: Beyond Black Box → Link https://t.co/1wif5AHX5X
#XAI #AIadoption #InterpretableML #AI2025 #MachineLearning
Our lab got two papers accepted at #ECMLPKDD2025 on the topics of #Interpretability for Spiking NNs and self-supervised learning with embedded interpretability. Congrats to Jasper, @behzadikhormuji, & Fabian. #SNN #ML #neuromorphic #xai #interpretableML @IDLabResearch #UAntwerp
And what you would notice in a text from someone with early dementia? Read the paper & let us know what you think matters.
#NLP #LLM #AI #Dementia #CognitiveHealth #ExplainableAI #InterpretableML #AI4Good #Alzheimers
Our #ICLR paper, “Efficient & Accurate Explanation Estimation with Distribution Compression” made the top 5.1% of submissions and was selected as a Spotlight! Congrats to the first author @hbaniecki #xAI #interpretableML
Paper: https://t.co/bd21S0zWpu
🚨 Are you at #INFORMS2024? Don't miss our session on Emerging Trends in Interpretable Machine Learning today at 2:15 PM! 🌟 Our speakers will dive into theoretical and applied aspects of interpretability and model multiplicity.
💡#InterpretableML #TrustworthyAI #Multiplicity
Special thanks to our supporting institutions: @UMI_Lab_AI
@unipotsdam
@LeibnizATB
@bifoldberlin
@FraunhoferHHI
@TUBerlin
#InterpretableML #MechInterp #ExplainableAI
We are looking for a PhD in Interpretable Machine Learning and Explainable AI @LMU_Muenchen.
Apply now at https://t.co/0r2EiV5dz7!
@XAI_Research #PhD #XAI #MachineLearning #Statistics #ExplainableAI #DataScience #InterpretableML
#ICML #BayesianDeepLearning #InterpretableML #FoundationModel Ever wondered what concepts vision foundation models (e.g., ViTs) learn and use to make predictions?
🚀Just published our new paper in @EarthsFutureEiC! 🌍 We propose how #InterpretableML can be more broadly and effectively integrated into geoscientific research, highlighting key do's and don'ts when using IML for process understanding. Check it out: https://t.co/y7H7LWrGsS
#BayesianDeepLearning #InterpretableML #ConceptInterpretation #HumanAICollaboration Achieving the balance between accuracy and interpretability in machine learning models is a notable challenge. Models that are accurate often lack interpretability,
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