Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
How important are activation functions in regression and classification? A survey, performance comparison, and future directions
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2209.02681.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T12:39:09.308337Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T12:59:52.081520Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation bb50c474-12e0-49d8-a0b5-880a7269d3d6 · inbound
Hybrid activation functions for deep neural networks: S3 and S4 -- a novel approach to gradient flow optimization cites this paper.
Hybrid activation functions for deep neural networks: S3 and S4 -- a novel approach to gradient flow optimization How important are activation functions in regression and classification? A survey, performance comparison, and future directions
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T12:39:09.308337Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6630d072-c94b-4099-8c24-514ad28773d4 · inbound
Identifying structural design principles shaping the computational abilities of recurrent neural networks cites this paper.
Identifying structural design principles shaping the computational abilities of recurrent neural networks How important are activation functions in regression and classification? A survey, performance comparison, and future directions
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T12:59:52.082992Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.