#interpretableml search results
The first version of my online book on Interpretable Machine Learning is out! christophm.github.io/interpretable-… I am very excited to release it. It's a guide for making machine learning models explainable. #interpretableML #iml #ExplainableAI #xai #MachineLearning #DataScience
Giving a talk on Explainable AI in Healthcare at @CTSICN in hour #responsibleAI #InterpretableML #explainableAI
We are having a mini-session in #causality at #pbdw2019 with first two talks by Rich Caruana and Yi Luo! #interpretableML #radonc @UMichRadOnc @MSFTResearch
Looking forward to the 1st #XAI day webinar tomorrow, Sept. 3rd, at @DIAL_UniCam. Many thanks to the speakers @grau_isel, Eric S. Vorm and @leilanigilpin who will talk about the essentials of #interpretableML and its applications.
The first session of oral presentations has concluded, very interesting talks from A. Himmelhuber (Siemens) and M. Couceiro (U. Lorraine) on the topics GNN explanations and tranferability of analogies learned via DNNs. #AIMLAI @ECMLPKDD 2021. #xai #interpretableML
I've created a short demo in #rstats on how to enforce monotonic constraints in H2O #AutoML / Stacked Ensembles. #InterpretableML #xai Thanks to @Navdeep_Gill_ for the partial dependence plots! @h2oai 👉 gist.github.com/ledell/91beb92…
Our paper "NoiseGrad: enhancing explanations by introducing stochasticity to model weights" has been accepted at #AAAI2022 🎉 See you (fingers crossed) in Canada 🇨🇦 arxiv.org/abs/2106.10185 #ML #InterpretableML #XAI
#KDD2019 keynote speaker @CynthiaRudin on #InterpretableML - recidivism models all perform about the same & Complicated models are preferred because they are profitable #explainableAI @kdd_news
Relying on XGBoost/RF feature importances to interpret your model? Read this first towardsdatascience.com/interpretable-… You are probably reporting misleading conclusions #XAI #interpretableML
.@aghaei_sina will be presenting our paper on strong formulations for optimal classification trees tomorrow at #MIP2020 — joint work with the one and only @GomezAndres8 #MIPforMachineLearning #InterpretableML
#AIMLAI @ECMLPKDD 2021 has started. Right now Prof Zhou (@zhoubolei) from CUHK is giving a keynote highlighting the efforts of his team towards making deep AI models think like humans. #xai #interpretableml #ai
We have 2 open #PhD positions where fellows will work with 24/7 recordings of physical activity: one focusing on #InterpretableML and one on the risk of common non-communicable diseases. Plz share the post in your network & help us find talented students: s.ntnu.no/labda
#ECDA2018 @hnfpb @RealGabinator thanks! Nice talk and nice overview about explanation methods in #DNN. #InterpretableML
A sensitivity analysis of a regression model of ocean temperature @RachelaFurner @DanJonesOcean @EmilyShuckburgh et al → doi.org/10.1017/eds.20… #OceanTemperature #DataScience #InterpretableML #ML #Oceanography #RegressionModel #ClimateModels #ClimateScience #MachineLearning
Yes, we did it again :-) Benedikt Bönninghoff, Robert Nickel and I - again at 1st place in the 2021 PAN@CLEF author identification challenge pan.webis.de/clef21/pan21-w… #interpretableML #machinelearning @HGI_Bochum @CASA_EXC @ika_rub @ruhrunibochum
NoiseGrad allows to enhance local explanations of #ML models by introducing stochasticity to the weights. However, it is also possible to improve Global Explanations! Check out by yourself! #XAI #InterpretableML github.com/understandable…
RT SHAP for Categorical Features dlvr.it/SSYRVn #interpretableml #machinelearning #shap #datascience #explainableai
RT AI Explainability Requires Robustness dlvr.it/SDtxqw #machinelearning #explainableai #interpretableml #adversarialattack
CALL FOR PAPERS AND ABSTRACTS “Explainable Artificial Intelligence For Unveiling The Brain: From The Black-Box To The Glass-Box” BrainInformatics2023 #explainableAI #explainableML #interpretableML #XAI #ArtificialIntelligence #MachineLearning #neuroscience #neuroimaging #brain
Paper: nature.com/articles/s4200… Code: github.com/ohsu-cedar-com… #InterpretableML #AIinCancer #SingleCell #MultiOmics #InterpretableAI #CancerGenomics #OpenScience #Bioinformatics #ComputationalBiology #MachineLearning
#CVPR2025 #TrustworthyML #InterpretableML #GenAI #AI #MachineLearning #AIResearch #DeepLearning #ComputerVision
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: arxiv.org/abs/2406.18334
🚨 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
#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: agupubs.onlinelibrary.wiley.com/doi/full/10.10…
#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,
🌟 Seeking Postdoc Position in Interpretable Machine Learning! 🤖🔍 Strong ML background, eager to contribute to cutting-edge research. Looking for opportunities to collaborate and make an impact. #InterpretableML #Postdoc #AIResearch #phdchat
Two of my PRs are now merged with PySR: now you can use "min", "max" and "round" operators without any explicit sympy mapping. PySR is a Python interface to a Julia backend for Symbolic Regression #interpretableML github.com/MilesCranmer/P…
We have in mind several directions to further investigate the topic in the future and we are excited about it, so we encourage and welcome any feedback or exchange of ideas on the paper’s topic! #deeplearning #explainableAI #interpretableML /5
#ICML2023 #BayesDL #InterpretableML Can we train self-interpretable time series models that generate actionable explanations? Come check out our Counterfactual Time Series (CounTS) in the oral session C2 at 3pm~4:30pm, July 27 and poster session 11:00am~1:30pm on July 25, Hall 1.
2️⃣ "Interpretable Machine Learning: A Guide for Making Black Box Models Explainable" by Christoph Molnar. Explore techniques to understand and interpret complex machine learning models, ensuring transparency and trust in AI systems. #InterpretableML #ExplainableAI
We have 2 open #PhD positions where fellows will work with 24/7 recordings of physical activity: one focusing on #InterpretableML and one on the risk of common non-communicable diseases. Plz share the post in your network & help us find talented students: s.ntnu.no/labda
CALL FOR PAPERS AND ABSTRACTS “Explainable Artificial Intelligence For Unveiling The Brain: From The Black-Box To The Glass-Box” BrainInformatics2023 #explainableAI #explainableML #interpretableML #XAI #ArtificialIntelligence #MachineLearning #neuroscience #neuroimaging #brain
The first version of my online book on Interpretable Machine Learning is out! christophm.github.io/interpretable-… I am very excited to release it. It's a guide for making machine learning models explainable. #interpretableML #iml #ExplainableAI #xai #MachineLearning #DataScience
We are having a mini-session in #causality at #pbdw2019 with first two talks by Rich Caruana and Yi Luo! #interpretableML #radonc @UMichRadOnc @MSFTResearch
RT SHAP for Categorical Features dlvr.it/SSYRVn #interpretableml #machinelearning #shap #datascience #explainableai
A sensitivity analysis of a regression model of ocean temperature @RachelaFurner @DanJonesOcean @EmilyShuckburgh et al → doi.org/10.1017/eds.20… #OceanTemperature #DataScience #InterpretableML #ML #Oceanography #RegressionModel #ClimateModels #ClimateScience #MachineLearning
RT AI Explainability Requires Robustness dlvr.it/SDtxqw #machinelearning #explainableai #interpretableml #adversarialattack
RT The Relationship between Interpretability and Fairness dlvr.it/SS655s #interpretableml #datascience #explainableai #algorithmfairness
RT Analysing NYC Yellow Taxi Trip Records with InterpretML dlvr.it/Sgs913 #interpretableai #interpretableml #datascience #machinelearning
#AIMLAI @ECMLPKDD 2021 has started. Right now Prof Zhou (@zhoubolei) from CUHK is giving a keynote highlighting the efforts of his team towards making deep AI models think like humans. #xai #interpretableml #ai
Giving a talk on Explainable AI in Healthcare at @CTSICN in hour #responsibleAI #InterpretableML #explainableAI
The first session of oral presentations has concluded, very interesting talks from A. Himmelhuber (Siemens) and M. Couceiro (U. Lorraine) on the topics GNN explanations and tranferability of analogies learned via DNNs. #AIMLAI @ECMLPKDD 2021. #xai #interpretableML
An exponential growth in the application of machine learning (ML) models. But several times I run into this. #Data #InterpretableML #BlackBoxModels #ArtificialIntelligence
#ECDA2018 @hnfpb @RealGabinator thanks! Nice talk and nice overview about explanation methods in #DNN. #InterpretableML
#KDD2019 keynote speaker @CynthiaRudin on #InterpretableML - recidivism models all perform about the same & Complicated models are preferred because they are profitable #explainableAI @kdd_news
Interpreting predictions made by a black box model with SHAP: bit.ly/3iO1vPT. Amazing work @scottlundberg! This kind of tool opens a whole new world of possibilities for practical AI applications. #interpretableML #MachineLearning #DataScience #SHAP #Python
I've created a short demo in #rstats on how to enforce monotonic constraints in H2O #AutoML / Stacked Ensembles. #InterpretableML #xai Thanks to @Navdeep_Gill_ for the partial dependence plots! @h2oai 👉 gist.github.com/ledell/91beb92…
#SpecialIssue "Foundations and Challenges of Interpretable ML", edited by Prof. Dr. Valera and Dr. Pradier, deadline has been extended to 31 July 2021. Look forward to your submissions! mdpi.com/journal/inform… #InterpretableML #probabilisticsML
Yes, we did it again :-) Benedikt Bönninghoff, Robert Nickel and I - again at 1st place in the 2021 PAN@CLEF author identification challenge pan.webis.de/clef21/pan21-w… #interpretableML #machinelearning @HGI_Bochum @CASA_EXC @ika_rub @ruhrunibochum
D4S Sunday Briefing #113 - bit.ly/3fedHsP This week we cover #InterpretableML, #ML, #WikiGraphs, #Scientific #Computing Subscribe: bit.ly/2YaiZLc and never miss an update! #BigData #DeepLearning
#Newpaper [Article] Deterministic Local Interpretable Model-Agnostic Explanations for Stable Explainability #ExplainableArtificialIntelligence (XAI) #InterpretableML 👉Please find more details via: mdpi.com/2504-4990/3/3/… @MAKE_MDPI
Relying on XGBoost/RF feature importances to interpret your model? Read this first towardsdatascience.com/interpretable-… You are probably reporting misleading conclusions #XAI #interpretableML
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