·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Meta AI director Rohit Patel leaves to take on Microsoft Office and Google Workspace1h◆Apple is adding an AI chatbot to Pages, Keynote, and Numbers2h◆Japan internet giant GMO says hackers posted stolen customer data2h◆Opera introduces a new web standard to let users deploy AI locally in their browser3h◆General Compute raises $100 million Series A, countering the neocloud disaster narrative3h◆Industrial Intelligence: The next growth opportunity for manufacturing5h◆Nvidia backs Indian startup helping companies run AI models with fewer GPUs5h◆Data center backlash is uniting America6h◆When Generated Information Returns: Error Persistence in LLM-Mediated Information Ecosystems12h◆Query-Driven Learning for Lifted Reasoning12h◆The Social World Model Evaluation Gap12h◆Conviction Without Evidence: Verdict Stability Is Independent of Visual Grounding in Medical Vision--Language Models12h◆The Value of Memory in Language Agents12h◆Synthetic linguistic data12h◆MAGNET: Manifold-Aware Graph Diffusion Network for Connectome Generation12h◆NewsBench: Expert-Grounded Evaluation of Epistemic Quality in AI News Reporting12h◆RobotAgentBench: Towards Open-world Robot Autonomy12h◆Folding Pooled Usage Examples into the Tool Index Lowers Retrieval of Unused Tools12h◆Compatible Likelihoods for Flow Matching on Manifolds12h◆Foundations of the Scaling Law12h◆Meta AI director Rohit Patel leaves to take on Microsoft Office and Google Workspace1h◆Apple is adding an AI chatbot to Pages, Keynote, and Numbers2h◆Japan internet giant GMO says hackers posted stolen customer data2h◆Opera introduces a new web standard to let users deploy AI locally in their browser3h◆General Compute raises $100 million Series A, countering the neocloud disaster narrative3h◆Industrial Intelligence: The next growth opportunity for manufacturing5h◆Nvidia backs Indian startup helping companies run AI models with fewer GPUs5h◆Data center backlash is uniting America6h◆When Generated Information Returns: Error Persistence in LLM-Mediated Information Ecosystems12h◆Query-Driven Learning for Lifted Reasoning12h◆The Social World Model Evaluation Gap12h◆Conviction Without Evidence: Verdict Stability Is Independent of Visual Grounding in Medical Vision--Language Models12h◆The Value of Memory in Language Agents12h◆Synthetic linguistic data12h◆MAGNET: Manifold-Aware Graph Diffusion Network for Connectome Generation12h◆NewsBench: Expert-Grounded Evaluation of Epistemic Quality in AI News Reporting12h◆RobotAgentBench: Towards Open-world Robot Autonomy12h◆Folding Pooled Usage Examples into the Tool Index Lowers Retrieval of Unused Tools12h◆Compatible Likelihoods for Flow Matching on Manifolds12h◆Foundations of the Scaling Law12h◆
News/Randomized neural operator for parametric PDEs with fast training and conformal uncertainty quantification
arxiv
PublishedJune 30, 2026 at 4:00 AM
▲bullish

Randomized neural operator for parametric PDEs with fast training and conformal uncertainty quantification

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2606.29440v1 Announce Type: new Abstract: Repeatedly solving parametric PDEs is essential for uncertainty quantification, design optimization and inverse problems, but conventional neural operators require expensive non-convex training. We introduce PCA--RaNN, a randomized latent neural operat

Stay posted· Newsletter

Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.

// no spam · unsubscribe one-click · free forever

Your email is used only to send The Bubble Brief. Privacy policy

Discussion
Mentioned models
01
  • 01
    PCA--RaNN
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#machine-learning#numerical-analysis#optimization#uncertainty-quantification

No replies yet. Be first.

Mentioned models
01
  • 01
    PCA--RaNN
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#machine-learning#numerical-analysis#optimization#uncertainty-quantification

Related coverage

More from ARXIV
arxivWhen Generated Information Returns: Error Persistence in LLM-Mediated Information Ecosystems12harxivQuery-Driven Learning for Lifted Reasoning12harxivThe Social World Model Evaluation Gap12harxivConviction Without Evidence: Verdict Stability Is Independent of Visual Grounding in Medical Vision--Language Models12h
The Bubble Brief
MON · WED · FRI

Read machine-learning insights every Monday, Wednesday and Friday — top movers, new models, story of the week.

// no spam · unsubscribe one-click · free forever

Your email is used only to send The Bubble Brief. Privacy policy

Originally published on arxiv ↗
PrivacyTermsRefundsLegal notice|AboutMethodologyContact

© 2026 Databubble

Built by Marouane Gazouzi · Readyo, AI interview coach

HomeModelsNews