·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Google’s AI search is rapidly becoming the default, new data shows12m◆Power up your AI infrastructure! A first look at the Smart Systems Stage agenda at TechCrunch Disrupt 202639m◆This $9 key physically locks your most addictive apps43m◆Ilya Sutskever’s Safe Superintelligence partners with Nvidia to scale its AI research1h◆Enigma raises $70M to make controlling a robot as easy as adjusting the volume3h◆Nvidia, Microsoft launch open AI security alliance — without OpenAI, Google, or Anthropic4h◆The path to artificial superintelligence4h◆Closing the data loop in AI-driven drug discovery4h◆Building the enterprise environment for agentic AI4h◆NVIDIA Cosmos-H-Dreams: Bringing Real-Time Generative Simulation to Surgical Robotics6h◆A Consensus-Based Framework for Relative Preference Evaluation of Large Language Models12h◆Probing Latent Colombian Identity Inferences in Qwen2.5-7B with Natural Language Autoencoders12h◆Data Quality over Capacity: Internalizing Documents into LoRA Adapters for Closed-Book QA12h◆Enjoy Your Talk: A Human-Centered Benchmark for Multi-Turn Dialogue with Decoupled User Simulation, Target Modeling, and Judging12h◆Multi-Mask Diffusion Language Models for Few-Step Generation12h◆Solar Open 2 Technical Report12h◆The Geometry of Personality: Activation Steering with Jungian Cognitive Functions12h◆Self-Guided Process Reward Optimization with Redefined Step-wise Advantage for Process Reinforcement Learning12h◆H$^2$SD: Hybrid Hindsight Self-Distillation12h◆LunarFM: A Shared Multimodal Representation of the Moon's Surface12h◆Google’s AI search is rapidly becoming the default, new data shows12m◆Power up your AI infrastructure! A first look at the Smart Systems Stage agenda at TechCrunch Disrupt 202639m◆This $9 key physically locks your most addictive apps43m◆Ilya Sutskever’s Safe Superintelligence partners with Nvidia to scale its AI research1h◆Enigma raises $70M to make controlling a robot as easy as adjusting the volume3h◆Nvidia, Microsoft launch open AI security alliance — without OpenAI, Google, or Anthropic4h◆The path to artificial superintelligence4h◆Closing the data loop in AI-driven drug discovery4h◆Building the enterprise environment for agentic AI4h◆NVIDIA Cosmos-H-Dreams: Bringing Real-Time Generative Simulation to Surgical Robotics6h◆A Consensus-Based Framework for Relative Preference Evaluation of Large Language Models12h◆Probing Latent Colombian Identity Inferences in Qwen2.5-7B with Natural Language Autoencoders12h◆Data Quality over Capacity: Internalizing Documents into LoRA Adapters for Closed-Book QA12h◆Enjoy Your Talk: A Human-Centered Benchmark for Multi-Turn Dialogue with Decoupled User Simulation, Target Modeling, and Judging12h◆Multi-Mask Diffusion Language Models for Few-Step Generation12h◆Solar Open 2 Technical Report12h◆The Geometry of Personality: Activation Steering with Jungian Cognitive Functions12h◆Self-Guided Process Reward Optimization with Redefined Step-wise Advantage for Process Reinforcement Learning12h◆H$^2$SD: Hybrid Hindsight Self-Distillation12h◆LunarFM: A Shared Multimodal Representation of the Moon's Surface12h◆
News/On-board Telemetry Monitoring in Autonomous Satellites: Challenges and Opportunities
arxiv
PublishedApril 10, 2026 at 4:00 AM
—neutral

On-board Telemetry Monitoring in Autonomous Satellites: Challenges and Opportunities

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

arXiv:2604.08424v1 Announce Type: cross Abstract: The increasing autonomy of spacecraft demands fault-detection systems that are both reliable and explainable. This work addresses eXplainable Artificial Intelligence for onboard Fault Detection, Isolation and Recovery within the Attitude and Orbit Co

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

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

Discussion
Mentioned models
01
  • 01
    convolutional autoencoder
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#explainability#anomaly-detection#spacecraft#fault-detection

No replies yet. Be first.

Mentioned models
01
  • 01
    convolutional autoencoder
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#explainability#anomaly-detection#spacecraft#fault-detection

Related coverage

More from ARXIV
arxivA Consensus-Based Framework for Relative Preference Evaluation of Large Language Models12harxivProbing Latent Colombian Identity Inferences in Qwen2.5-7B with Natural Language Autoencoders12harxivData Quality over Capacity: Internalizing Documents into LoRA Adapters for Closed-Book QA12harxivEnjoy Your Talk: A Human-Centered Benchmark for Multi-Turn Dialogue with Decoupled User Simulation, Target Modeling, and Judging12h
The Bubble Brief
WEEKLY

Read explainability insights every Tuesday — top movers, new releases, story of the week.

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

Originally published on arxiv ↗
HomeModelsNews