·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Jensen Huang and the decline of the visionary showman founder CEO3h◆Mach2: Scientific Discovery Platform with Deterministic Execution Constraints10h◆OverServe: Resource Amplification Attacks on SaaS Agents via Tool--Prompt Co-Design10h◆CFGComposer: Compositional Audio-Text-to-Motion Generation via Copula Score Correction10h◆Multi-View 3D Reconstruction Using V-JEPA Features10h◆GingivitisSeg: A Public Dataset and Comparative Benchmark for Gingivitis Segmentation in Intraoral Images10h◆Can Model Answer Probabilities Represent Survey Populations? Conditional Prediction and Joint Validity in Jev Survey Simulation10h◆Contrastive Bootstrap Representation Learning for Label-Efficient Agricultural Image Classification10h◆SO-Arena: Benchmarking the Capability Spectrum and Reliability of System One Models10h◆The BEATS Dataset: Towards Understanding Music-Physiology Dynamics in Real-World Scenarios10h◆RESYNC: Residual Latent-State Synchronization for Deadline-Bound Streaming Inference10h◆LEAP: Supercharging LLMs for Formal Mathematics with Agentic Frameworks10h◆Do More Modalities Always Help? A Geometric Perspective on Missing-Modality Robustness10h◆Which Buildings Are Artificial Intelligence-Ready? A Measurement-Based Assessment Framework for AI Question Answering and Actuation10h◆Catch-Only-One: Non-Transferable Examples for Model-Specific Authorization10h◆DAISY: Fault-Guided Assertion Inference for Dafny10h◆Individualized Algorithmic Advice as a Strategic Signal on Competitive Markets10h◆Learning pharmacokinetic dynamics with structured neural ODEs for precision dosing10h◆ANCRe: Adaptive Neural Connection Reassignment for Efficient Depth Scaling10h◆Assessing Per-Sample Membership Inference Vulnerability without Retraining10h◆Jensen Huang and the decline of the visionary showman founder CEO3h◆Mach2: Scientific Discovery Platform with Deterministic Execution Constraints10h◆OverServe: Resource Amplification Attacks on SaaS Agents via Tool--Prompt Co-Design10h◆CFGComposer: Compositional Audio-Text-to-Motion Generation via Copula Score Correction10h◆Multi-View 3D Reconstruction Using V-JEPA Features10h◆GingivitisSeg: A Public Dataset and Comparative Benchmark for Gingivitis Segmentation in Intraoral Images10h◆Can Model Answer Probabilities Represent Survey Populations? Conditional Prediction and Joint Validity in Jev Survey Simulation10h◆Contrastive Bootstrap Representation Learning for Label-Efficient Agricultural Image Classification10h◆SO-Arena: Benchmarking the Capability Spectrum and Reliability of System One Models10h◆The BEATS Dataset: Towards Understanding Music-Physiology Dynamics in Real-World Scenarios10h◆RESYNC: Residual Latent-State Synchronization for Deadline-Bound Streaming Inference10h◆LEAP: Supercharging LLMs for Formal Mathematics with Agentic Frameworks10h◆Do More Modalities Always Help? A Geometric Perspective on Missing-Modality Robustness10h◆Which Buildings Are Artificial Intelligence-Ready? A Measurement-Based Assessment Framework for AI Question Answering and Actuation10h◆Catch-Only-One: Non-Transferable Examples for Model-Specific Authorization10h◆DAISY: Fault-Guided Assertion Inference for Dafny10h◆Individualized Algorithmic Advice as a Strategic Signal on Competitive Markets10h◆Learning pharmacokinetic dynamics with structured neural ODEs for precision dosing10h◆ANCRe: Adaptive Neural Connection Reassignment for Efficient Depth Scaling10h◆Assessing Per-Sample Membership Inference Vulnerability without Retraining10h◆
News/Learning-Based Interpolation of Detector Gaps in Photon-Counting X-ray Imaging
arxiv
PublishedNovember 14, 2026 at 5:00 AM

Learning-Based Interpolation of Detector Gaps in Photon-Counting X-ray Imaging

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

arXiv:2611.15614v1 Announce Type: cross Abstract: Image detectors assembled from tiled modules have physical gaps in the field of view that must be filled before downstream processing such as phase retrieval or tomographic reconstruction. Unlike natural-image inpainting, detector-gap interpolation m

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
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivMach2: Scientific Discovery Platform with Deterministic Execution Constraints10harxivOverServe: Resource Amplification Attacks on SaaS Agents via Tool--Prompt Co-Design10harxivCFGComposer: Compositional Audio-Text-to-Motion Generation via Copula Score Correction10harxivMulti-View 3D Reconstruction Using V-JEPA Features10h
The Bubble Brief
MON · WED · FRI

Read AI 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