Verified claim · AI-ML · 100% confidence
Adam optimizer introduced in paper: Adam: A Method for Stochastic Optimization (Kingma, Ba, 2014).
Last verified 2026-05-16 · Methodology veritas-v0.1 · dffbe905003cc581
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Structured fields
- Subject
- Adam optimizer
- Predicate
introduced_in_paper- Object
- Adam: A Method for Stochastic Optimization (Kingma, Ba, 2014)
- Confidence
- 100%
- Tags
- adam · optimizer · foundational · kingma · 2014 · iclr
Sources (2)
[1] preprint · arXiv (Kingma, Ba) · 2014-12-22
Adam: A Method for Stochastic Optimization“We introduce Adam, an algorithm for first-order gradient-based optimization of stochastic objective functions, based on adaptive estimates of lower-order moments.”
[2] peer reviewed · OpenReview / ICLR · 2015-05-07
Adam (ICLR 2015 proceedings)
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Yes — SourceScore verified this claim with 100% confidence as of 2026-05-16. The verification uses 2 primary sources cross-referenced against the SourceScore methodology (version veritas-v0.1). Full source list + signed JSON envelope linked below.
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Evidence comes from 2 primary sources: arXiv (Kingma, Ba), OpenReview / ICLR. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/dffbe905003cc581.json includes an HMAC-SHA256 signature for audit verification.
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// "Adam optimizer introduced in paper: Adam: A Method for Stochastic Optimization (Kingma, Ba, 2014)."Python
import httpx
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# "Adam optimizer introduced in paper: Adam: A Method for Stochastic Optimization (Kingma, Ba, 2014)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_adam_optimizer_fact() -> dict:
"""Fetch the verified SourceScore claim for Adam optimizer."""
r = httpx.get("https://sourcescore.org/api/v1/claims/dffbe905003cc581.json")
return r.json()