Verified claim · AI-ML · 82% confidence
Maxout introduced in paper: Maxout Networks (Goodfellow et al., 2013).
Last verified 2026-06-02 · Methodology veritas-v0.1 · 5d5408d170cebe41
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Structured fields
- Subject
- Maxout
- Predicate
introduced_in_paper- Object
- Maxout Networks (Goodfellow et al., 2013)
- Confidence
- 82%
- Tags
- maxout · activation-function · dropout · goodfellow · bengio · foundational · 2013
Sources (2)
[1] preprint · arXiv (Ian J. Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron Courville, Yoshua Bengio) · 2013-02-18
Maxout Networks“We define a simple new model called maxout (so named because its output is the max of a set of inputs, and because it is a natural companion to dropout) designed to both facilitate optimization by dropout and improve the accuracy of dropout's fast approximate model averaging technique.”
[2] docs · Hugging Face
Maxout Networks (Hugging Face Papers)Hugging Face is rated by SourceScore — see its reliability →
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Maxout introduced in paper: Maxout Networks (Goodfellow et al., 2013). — SourceScore Claim 5d5408d170cebe41 (verified 2026-06-02). https://sourcescore.org/api/v1/claims/5d5408d170cebe41.jsonEmbed this claim
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cURL
curl https://sourcescore.org/api/v1/claims/5d5408d170cebe41.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/5d5408d170cebe41.json");
const envelope = await r.json();
console.log(envelope.claim.statement);
// "Maxout introduced in paper: Maxout Networks (Goodfellow et al., 2013)."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/5d5408d170cebe41.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "Maxout introduced in paper: Maxout Networks (Goodfellow et al., 2013)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_maxout_fact() -> dict:
"""Fetch the verified SourceScore claim for Maxout."""
r = httpx.get("https://sourcescore.org/api/v1/claims/5d5408d170cebe41.json")
return r.json()