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Verified claim · AI-ML · 100% confidence

Batch Normalization introduced in paper: Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (Ioffe & Szegedy, 2015).

Last verified 2026-05-16 · Methodology veritas-v0.1 · 56c451642ab41e68

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Structured fields

Subject
Batch Normalization
Predicate
introduced_in_paper
Object
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (Ioffe & Szegedy, 2015)
Confidence
100%
Tags
batch-normalization · regularization · training · foundational · 2015 · icml · google

Sources (2)

  1. [1] preprint · arXiv (Ioffe, Szegedy) · 2015-02-11

    Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
    “We refer to this phenomenon as internal covariate shift, and address the problem by normalizing layer inputs. Our method draws its strength from making normalization a part of the model architecture and performing the normalization for each training mini-batch.”
  2. [2] peer reviewed · PMLR / ICML · 2015-07-07

    Batch Normalization (ICML 2015)

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Batch Normalization introduced in paper: Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (Ioffe & Szegedy, 2015). — SourceScore Claim 56c451642ab41e68 (verified 2026-05-16). https://sourcescore.org/api/v1/claims/56c451642ab41e68.json

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Python

import httpx r = httpx.get("https://sourcescore.org/api/v1/claims/56c451642ab41e68.json") envelope = r.json() print(envelope["claim"]["statement"]) # "Batch Normalization introduced in paper: Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (Ioffe & Szegedy, 2015)."

LangChain (retrieve-then-cite)

from langchain_core.tools import tool import httpx @tool def get_batch_normalization_fact() -> dict: """Fetch the verified SourceScore claim for Batch Normalization.""" r = httpx.get("https://sourcescore.org/api/v1/claims/56c451642ab41e68.json") return r.json()
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