🚀 The official schedule for the 𝟱𝘁𝗵 #𝗫𝗔𝗜𝟰𝗖𝗩 𝗪𝗼𝗿𝗸𝘀𝗵𝗼𝗽 𝗮𝘁 @cvprconference.bsky.social is here! 🗓️✨See you in Denver on June 3rd, 2026, 8:00 AM - 1:00 PM (MDT)! 🏔️👋 #CVPR2026 xai4cv-workshop.github.io/xai4cv2026/

The countdown is on!⏳We are in the last week for rolling submissions to the Non-Proceedings Track. If you are working on #XAI, we want to see your research at our 5th-anniversary #XAI4CV workshop at @cvprconference.bsky.social #CVPR2026 xai4cv-workshop.github.io/xai4cv2026/

Celebrating 5 years of the #XAI4CV Workshop at @cvprconference.bsky.social! The Non-Proceedings Track is open until April 7. Don't miss your chance to submit your latest research in #XAI—from interpretable-by-design to multimodal models and join us #CVPR2026 xai4cv-workshop.github.io/xai4cv2026/

The #XAI4CV workshop lineup has been revealed!🚀Celebrate 5 years at @cvprconference.bsky.social with researchers at the forefront of #XAI + a tutorial on concept-based interpretability in foundation models. Papers&demos across 2 tracks accepted! #CVPR2026 xai4cv-workshop.github.io/xai4cv2026/

We are thrilled to bring the #XAI4CV Workshop back to @cvprconference.bsky.social , celebrating its 5th Anniversary!🚀Submit your latest research in #XAI. We accept papers & demos across 2 tracks! #CVPR2026 xai4cv-workshop.github.io/xai4cv2026/ Please repost🔁

🎓 We’re proud to announce that Jordi Cortés Andrés, one of our PhD students, just defended his thesis: "Regularization in Machine Learning: Advances for Earth Sciences". 🥳 Congratulations on reaching this important milestone in your research journey!

🌍 @ellis.eu #SummerSchool2025 in Jena on AI for Earth & Climate Sciences is underway 👩🏼‍🎓140 PhD students, 👨🏻‍💻13 keynote speakers & 🧑🏼‍🏫 23 tutors are diving into keynotes, hands-on sessions & collaborative projects—bridging #ML & geosciences 🌿🤖 www.ellis-jena.eu/summer-schoo...

✨ Despite #AI technological advances, persistent challenges persist in creating usable data for decision-makers in practice. Dr. Adams-Fuller, Dr. Glenn, & Dr. Fernández-Torres discuss challenges in weather preparedness. ncdp.columbia.edu/ncdp-perspec... @climate.columbia.edu @leapstc.bsky.social

🗣️Yesterday we kicked off #LPS25 with"Advanced AI for Extreme Event Analysis: Hands-on with the AIDE Toolbox" (María González & @miguelangelft.bsky.social). 🌍 About this tool: 💾 github.com/IPL-UV/AIDE/ 📜 tr.ee/AIDEToolbox ℹ️ aidextremes.readthedocs.io/en/latest/

🆕📰 New paper out that studies the #Calibration and the #Uncertainty of Deep Learning Models (DLM) for #Drought. ➡️ "Calibration and uncertainty quantification for deep learning-based drought detection" 🔗 Read it here: tr.ee/CalibrationAndUncertaintyQuantification

📣 IN ONE WEEK: Please join us for the next LEAP Wallerstein Panel Series on #AI + Extreme Weather Preparedness! ✨ "DATA + AI FOR DECISION-SUPPORT AND POLICY" ✨ 📆 Fri., 4/25/25 || 🕙 10a EST 📍 Virtual ℹ️ Info + RSVP: www.eventbrite.com/e/1286345206... #community #climateadaptation #climateresilience

Submit your latest work (papers, demos) in #XAI to the 4th Explainable AI for Computer Vision (XAI4CV) Workshop at #CVPR2025! Details: xai4cv.github.io/workshop_cvp... Submission Site: cmt3.research.microsoft.com/XAI4CV2025 @cvprconference.bsky.social @xai-research.bsky.social

Curious about the recent trends, key challenges, and novel research directions in #explainableAI for #remotesensing? Then check our review paper "Opening the Black Box: A Systematic Review on Explainable Artificial Intelligence in Remote Sensing" (lnkd.in/et9dvHpZ) published at the IEEE #GRSM.

🚨 New paper out in @naturecomms.bsky.social We review how #AI is transforming modeling & understanding extreme weather & climate events like floods, heatwaves, and wildfires🌍🔥💨 🔗Read it! isp-uv.short.gy/AIforExtreme...

Comment: Explainability can foster trust in the use of AI in geoscience @jesper.drams.ch @ecmwf.bsky.social @aifraunhoferhhi.bsky.social www.nature.com/articles/s41...

Explainability can foster trust in artificial intelligence in geoscience - Nature Geoscience

Uptake of explainable artificial intelligence (XAI) methods in geoscience is currently limited. We argue that such methods that reveal the decision processes of AI models can foster trust in their res...

nature.com

🌍 New paper: Generative networks for spatio-temporal #gap_filling of #Sentinel2 reflectances @esa.int. 🆓 Free access the first 50 days to the #ISPRS paper @elsevierconnect.bsky.social: isp-uv.short.gy/GapFillingSe... Work developed in the context of Xaida Project. #AI #EarthObservation

🌍 Climate extremes, such as compound heatwaves and droughts, are increasing in both frequency and intensity, yet predicting their impacts on terrestrial ecosystems remains a challenge. Machine learning holds promise, but traditional datasets often struggle to represent these rare events effectively.