#explanableai 搜尋結果
Huge accomplishment to our Applied ML Interns Sneha Desai and Angad Singh Kalra for presenting their work at the #ARIA2019 showcase tonight #transferlearning #explanableAI #UofT #AppliedComputing
How about some #explanableAI 🪟 ? The JS code generated from Catala programs can now log all the intermediate values it computed, as well as display the source code and legal location justifying the decisions it takes. Details for PL nerds 🤓: github.com/CatalaLang/cat…
MIT Taxonomy Helps Build #Explainability into the Components of #MachineLearning Models #ExplanableAI scitechdaily.com/mit-taxonomy-h…
The second paper by Cherepanov et al. teaches us about the importance of #explanableAI in #CyberSecurity and how #Datavisualization can help #VizSec #ieeevis
[#Portrait] Nous accueillons également au @Cercle_Nadi @NADI_institute Florence Nizette qui commence sa thèse en collaboration avec @uhasselt ! 🥳 Florence étudie l'impact d'une intelligence artificielle fiable (#trustedAI #explanableAI) sur les consommateurs. #Welcome
#AI can help make better and faster decisions in #HealthCare scenarios and more accurate diagnoses. Understand how health care industry is leveraging the #ExplanableAI model: hubs.la/Q01nbqtc0 #AkiraAI
Burn out? Try #ExplanableAI #xai. linkedin.com/posts/mit-tech…
Quickly build Explainable AI Dashboards that show the inner workings of so-called "blackbox" machine learning models! Check out the Explainer Dashboard by @oegedijk here: github.com/oegedijk/expla… #explanableai
#MICCAI2022 heads-up: @maximek3 will present our work on "Explaining Chest X-ray Pathologies in Natural Language" Read more: arxiv.org/abs/2207.04343 New data set: github.com/maximek3/MIMIC… @MICCAI_Society @bdi_oxford #medicalImaging #ExplanableAI #NaturalLanguageExplanation
ReAGent, a model-agnostic feature attribution method, is available in Inseq now, for both decoder-only and encoder-decoder. #ExplanableAI The paper is here: arxiv.org/pdf/2402.00794…
@InseqLib v0.6 is out now on PyPI! 🔥 New CLI command for context attribution (@gsarti_), new perturbation-based methods by @hmohebbi75 & @casszzx and optimizations incl. multi-gpu support! ⚡️ Huge shoutout to our contributors! ❤️ Release notes ⬇️ github.com/inseq-team/ins…
New paper from @maximek3 at al. on "Explaining Chest X-ray Pathologies in Natural Language" Read more: arxiv.org/abs/2207.04343 New data: github.com/maximek3/MIMIC… and join us at #MICCAI2022 @MICCAI_Society to hear more! #medicalImaging #ExplanableAI #NaturalLanguageExplanation
✨New Paper✨ at #MICCAI2022🩺 🔎 Explaining Chest X-ray Pathologies in Natural Language arxiv.org/abs/2207.04343 with @CorEmde, @oanacamb, Guy Parsons, @bwpapiez, and Thomas Lukasiewicz @UniofOxford #ML #MedicalImaging #Xray #XAI #NLProc (1/5)
Parents: if all your friends jump in the well, Will you too ? Kid: NO! Machine learning algorithm: YES! #ai #MachineLearning #explanableai
The need for Explainable AI (XAI): Why is XAI important? #explanableAI #XAI #decisionmaking #AI #espincorp e-spincorp.com/the-need-for-e…
Learn more about Graph-based feature models and their potential for explanation #explanableAI #KG @fujitsu_ie pyvandenbussche.info/2017/knowledge…
A right to explanation | The Alan Turing Institute bit.ly/2D5scyp #ExplanableAI
When you design your (AI) products that are grounded in ExplanableAI, you will have solved for reliableAI and responsibleAI. #aiproducts #explanableAI
Such important work on #AI interpretability, well captured in this interview. Thank you for this @_beenkim : #explanableAI #interpretability quantamagazine.org/been-kim-is-bu…
AI for dummys with great visuals! Introduction to #ExplanableAI @dtsbourg your my reference in that domain —> Understanding the AI black box journal.jp.fujitsu.com/en/2019/01/17/…
Do the “packs” come with manuals listing built-in pre-trained (traceable/explainable) decisions (ehm ... biases)? @Grady_Booch @Ew_Luger @frossi_t @Marenka @amel_bennaceur @yijun_yu @E_Letier #explanableAI #AI #traceability #ethics #MachineLearning
IBM launches pretrained @IBMWatson packs for industries zd.net/2I8djKA Training #AI on your business takes time. This will accelerate Watson deployments + shorten ‘time to value’, a long standing issue with the platform. @ZDNet & @ldignan #cto #cio #analytics @IBM
Today @dagstuhl Logic and Learning seminar. Sound reasoning and learning heve been fundamental to AI since the work of Turing; interactions between these fields are growing in relevance. #explanableAI #AI #neuralsymboliccomputing #machinelearning #logic #reasoning
Looking forward to advent of New Technologies in #GPTs 1. GPT for masses 2. GPT for Secure Government 3. AI Models from and for India 4. Regulatory Framework for AI 5. Institutionalisation of #ExplanableAI #AI
ReAGent, a model-agnostic feature attribution method, is available in Inseq now, for both decoder-only and encoder-decoder. #ExplanableAI The paper is here: arxiv.org/pdf/2402.00794…
@InseqLib v0.6 is out now on PyPI! 🔥 New CLI command for context attribution (@gsarti_), new perturbation-based methods by @hmohebbi75 & @casszzx and optimizations incl. multi-gpu support! ⚡️ Huge shoutout to our contributors! ❤️ Release notes ⬇️ github.com/inseq-team/ins…
The need for Explainable AI (XAI): Why is XAI important? #explanableAI #XAI #decisionmaking #AI #espincorp e-spincorp.com/the-need-for-e…
Huge accomplishment to our Applied ML Interns Sneha Desai and Angad Singh Kalra for presenting their work at the #ARIA2019 showcase tonight #transferlearning #explanableAI #UofT #AppliedComputing
The second paper by Cherepanov et al. teaches us about the importance of #explanableAI in #CyberSecurity and how #Datavisualization can help #VizSec #ieeevis
How about some #explanableAI 🪟 ? The JS code generated from Catala programs can now log all the intermediate values it computed, as well as display the source code and legal location justifying the decisions it takes. Details for PL nerds 🤓: github.com/CatalaLang/cat…
#AI can help make better and faster decisions in #HealthCare scenarios and more accurate diagnoses. Understand how health care industry is leveraging the #ExplanableAI model: hubs.la/Q01nbqtc0 #AkiraAI
MIT Taxonomy Helps Build #Explainability into the Components of #MachineLearning Models #ExplanableAI scitechdaily.com/mit-taxonomy-h…
#MICCAI2022 heads-up: @maximek3 will present our work on "Explaining Chest X-ray Pathologies in Natural Language" Read more: arxiv.org/abs/2207.04343 New data set: github.com/maximek3/MIMIC… @MICCAI_Society @bdi_oxford #medicalImaging #ExplanableAI #NaturalLanguageExplanation
New paper from @maximek3 at al. on "Explaining Chest X-ray Pathologies in Natural Language" Read more: arxiv.org/abs/2207.04343 New data: github.com/maximek3/MIMIC… and join us at #MICCAI2022 @MICCAI_Society to hear more! #medicalImaging #ExplanableAI #NaturalLanguageExplanation
✨New Paper✨ at #MICCAI2022🩺 🔎 Explaining Chest X-ray Pathologies in Natural Language arxiv.org/abs/2207.04343 with @CorEmde, @oanacamb, Guy Parsons, @bwpapiez, and Thomas Lukasiewicz @UniofOxford #ML #MedicalImaging #Xray #XAI #NLProc (1/5)
Quickly build Explainable AI Dashboards that show the inner workings of so-called "blackbox" machine learning models! Check out the Explainer Dashboard by @oegedijk here: github.com/oegedijk/expla… #explanableai
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