Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T13:49:25.803786Z
Paper Citation Record · LEDGER
As of 13 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2411.15931.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T13:49:25.803786Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
15 of 15 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 132023f8-4370-4e9f-9bff-2a801212f943 · outbound
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning
Reference 1
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7b27a28c-0f6c-4026-8603-9636d5c87a29 · outbound
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization Unresolved cited work
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation f59b4268-68ce-4712-80c0-04f0fca3cec1 · outbound
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization Unresolved cited work
Reference 8
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation acb29ea9-6d87-41f8-9440-59712b64dd90 · outbound
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization Self-supervised learning with rotation-invariant kernels
Reference 9
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 63d95287-08ad-4e73-a24e-2fdc364a1ee9 · outbound
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization For SimSiam, the semi-supervised experiments were not conducted in the original paper, and therefore we skip this in our experiments
Reference 13
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation c4e21e06-317a-4f46-96df-f0e75d8b5f4b · outbound
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization Unresolved cited work
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation da8c0acf-74cf-40a6-83c5-29f21457168e · outbound
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization Unresolved cited work
Reference 25
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 0d842627-b9d5-4095-97a8-2df1778f5b40 · outbound
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization Variance Covariance Regularization Enforces Pairwise Independence in Self-Supervised Representations
Reference 1947
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 99831a16-b25d-42b8-9e72-d9da02418bc2 · outbound
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization Spreading vectors for similarity search
Reference 2015
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8e86073d-adf6-4d3b-b5dc-8dcc5390b890 · outbound
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization Learning deep representations by mutual information estimation and maximization
Reference 2016
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2fc6974b-60e1-4f21-a90e-c15236a99f44 · outbound
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations
Reference 2018
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2e1a7a9b-c2a5-431f-bef7-8e8cca6ae7a0 · outbound
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization For continued pretraining, our criterion is applied to the projector embeddingsZ before the cluster assignment layer and before normalization after mapping through the CDF function
Reference 2020
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 5ff25881-dcfd-4499-8b45-cbd8aeadd02d · outbound
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization A new class of entropy estimators for multi-dimensional densities
Reference 2022
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation b68e99e9-f2cb-4863-87b4-e8f260aae541 · outbound
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization EMP-SSL: Towards Self-Supervised Learning in One Training Epoch
Reference 2023
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9718f461-1107-43fc-a41a-6887a0ce423a · outbound
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization
Reference 2024
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.