ArticleNature communications2025
Bayesian neural network with unified entropy source and synapse weights using 3D 16-layer Fe-diode array.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Article
- Coupled dual-channel memristors for hardware-native trustworthy Bayesian intelligence.Nature communications · 2026Article
- Stable Analog Weight Programming in Single-Crystalline van der Waals Ferroelectric Transistors for Reliable Computing-in-Memory.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Endurance Paradox in Hafnium-Oxide-Based Silicon-Channel Ferroelectric Transistors.ACS applied materials & interfaces · 2026Article
- Constraint aware and uncertainty informed QSAR modeling of Tetrahymena pyriformis toxicity using physicochemical descriptors.Scientific reports · 2026Article
- Hafnium-Based Ferroelectric Post-Moore Electronics: Device Physics, Integration Architectures, and Neuromorphic System Implementation.Nano-micro letters · 2026Review
- Gallium Nitride-Based Electrode Materials for Supercapacitors: From Wide Band Semiconductor to Energy Storage Platform.Small (Weinheim an der Bergstrasse, Germany) · 2026Review
- Noise Fingerprints as a Quantitative Order Parameter for Polarization- and Defect-Mediated Switching in Hafnia Ferroelectrics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- ALD-Derived WOACS applied electronic materials · 2026Article
- Investigation of Electron Transport Layer Influence on Asymmetric Bipolar Switching in Transparent BST-Based RRAM Devices.Micromachines · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Edge artificial intelligence systems require higher frequency due to intensive computational demands, while most traditional entropy sources decay with frequency. This work shows the physical properties of the Fe-diode devices are ideal for edge systems with high frequencies and dramatic temperature changes. The noise density of Fe-diode can be modified by the amplitude of the read voltage and remains stable at high frequencies and temperature fluctuations. A Bayesian neural network with Fe-diode devices is experimentally implemented in high-speed, high-density silicon-based chips. This hierarchical Bayesian neural network is demonstrated on 3D 16-layer Fe-diode array based on unified entropy source and 4-state synapse. Properties including high area efficiency, wide working temperature range, low energy in-situ training, high recognition accuracy are finally achieved.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.