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Paper Citation Record · LEDGER

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model

As of 17 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:1908.04537.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1908.04537 v2

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:47:02.535857Z

measured 58 of 58 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

58 of 58 outbound references displayed

  • verified exact2
  • verified fuzzy47
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f289fd95-9580-4ab8-a006-dc51536655a9 · outbound

This paper cites An introduction to MCMC for machine learning.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model An introduction to MCMC for machine learning

Reference 1

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Source-reported events for the cited work

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Observation 68c5479a-b7dc-49a7-aab8-5e26bd482519 · outbound

This paper cites Online choice of active learning algorithms.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Online choice of active learning algorithms

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation f4a84ff6-ddf7-4248-b4bf-d78283a1540f · outbound

This paper cites Variational algorithms for approximate Bayesian inference.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Variational algorithms for approximate Bayesian inference

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 273e2e06-fb50-4ad1-a636-e42f5a44a6c1 · outbound

This paper cites Expected information as expected utility.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Expected information as expected utility

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.157450Z digest=sha256:3dee84fd298dffcc6dfa46a7c4add9da8ad717da1bc284f728da25e8ffea6a78

Observation 3faa46ad-ce0b-4a33-9538-5427c53903d2 · outbound

This paper cites Active matrix completion.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Active matrix completion

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation f6ed0c56-f4c1-423b-b8a6-44c9e306f573 · outbound

This paper cites Bridging the gap between stochastic gradient MCMC and stochastic optimization.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Bridging the gap between stochastic gradient MCMC and stochastic optimization

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation c08cd5ca-8424-4e9a-a1c9-0a2b3cc6b64d · outbound

This paper cites Elements of information theory.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Elements of information theory

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:47:02.197901Z digest=sha256:32fc74395042e2dbf83b18b866529207703e404893475a3fad312f799cec52b1

Observation ccf20ddd-37c6-49d1-9a5d-dcc4f6f34e25 · outbound

This paper cites UCI machine learning repository, 2017.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model UCI machine learning repository, 2017

Reference 8

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raw_fallback, observed 2026-08-14T13:47:03.830032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 3b5a8d7c-dc98-4364-815b-2e9600a6118c · outbound

This paper cites Deep bayesian active learning with image data.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Deep bayesian active learning with image data

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation c648f18f-6287-4cf7-8d52-b48d19602840 · outbound

This paper cites The Movielens datasets: History and context.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model The Movielens datasets: History and context

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation f1f1ea18-e29c-4cc9-8326-9ce5999c0808 · outbound

This paper cites Multitask learning and benchmarking with clinical time series data.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Multitask learning and benchmarking with clinical time series data

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation fd4ad1a4-0b69-4fd2-845d-8d222ccbdb75 · outbound

This paper cites Inference in deep gaussian processes using stochastic gradient Hamiltonian Monte Carlo.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Inference in deep gaussian processes using stochastic gradient Hamiltonian Monte Carlo

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation c6cc24cf-138e-4856-b0a2-373f5191dfd4 · outbound

This paper cites Bayesian Active Learning for Classification and Preference Learning.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Bayesian Active Learning for Classification and Preference Learning

Reference 13

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no resolver link, observed 2026-08-14T13:47:02.236478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:47:02.236478Z digest=sha256:2d8576d1a540f98d4e83b2930273666967353670c1b3474034cb10f43b5fae55

Observation 0dde96fe-d15f-4932-9776-8a88fb238699 · outbound

This paper cites Cold-start active learning with robust ordinal matrix factorization.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Cold-start active learning with robust ordinal matrix factorization

Reference 14

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation b6686816-cd04-4706-8de3-a0ea26948308 · outbound

This paper cites Active Feature Acquisition with Supervised Matrix Completion.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Active Feature Acquisition with Supervised Matrix Completion

Reference 15

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local_arxiv, observed 2026-08-14T13:47:02.691866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 0a18a48f-125a-4210-a487-86bbe8838ce8 · outbound

This paper cites Classification with Costly Features using Deep Reinforcement Learning.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Classification with Costly Features using Deep Reinforcement Learning

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation bcf446d3-5192-4264-a0ec-06a095e3c4a6 · outbound

This paper cites MIMIC-III , a freely accessible critical care database.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model MIMIC-III , a freely accessible critical care database

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 1cbcb86a-47d9-47af-ba78-076d77771cbd · outbound

This paper cites An introduction to variational methods for graphical models.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model An introduction to variational methods for graphical models

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 67918499-affa-44ac-97f2-bf4e46530cda · outbound

This paper cites Selective supervision: Guiding supervised learning with decision-theoretic active learning.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Selective supervision: Guiding supervised learning with decision-theoretic active learning

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 28345a54-d993-4bbb-9736-9dd71672f1e2 · outbound

This paper cites Auto-encoding variational Bayes.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Auto-encoding variational Bayes

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 9948c385-cf8e-41c4-9fd2-dd92587a08c7 · outbound

This paper cites A utility-theoretic approach to privacy in online services.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model A utility-theoretic approach to privacy in online services

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 76a60797-1953-47a3-be4a-a4e0bf54aa72 · outbound

This paper cites Traffic updates: Saying a lot while revealing a little.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Traffic updates: Saying a lot while revealing a little

Reference 22

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 122b173d-851e-44d2-b379-28f3b24b1bb6 · outbound

This paper cites Knowing what to ask: A Bayesian active learning approach to the surveying problem.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Knowing what to ask: A Bayesian active learning approach to the surveying problem

Reference 23

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation e74772da-5c3a-47e6-8845-f475dff4e97f · outbound

This paper cites Preconditioned stochastic gradient Langevin dynamics for deep neural networks.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Preconditioned stochastic gradient Langevin dynamics for deep neural networks

Reference 24

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation eaaa32c6-c92c-44db-af07-80bcdb392e1b · outbound

This paper cites Approximate Inference: New Visions.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Approximate Inference: New Visions

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.318639Z digest=sha256:cf8da55bb28862a8a8d5354536a0a8ea36205a0ae7ead6e1fd4d1ca40cf26b09

Observation f2918017-5c87-4bc8-8c08-1e81f267a523 · outbound

This paper cites On a measure of the information provided by an experiment.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model On a measure of the information provided by an experiment

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.324508Z digest=sha256:da87474684492ff32ff008b9bb32a29d31927fd9d821d7cdbc9a3a12e5a33384

Observation 04b3c003-bf0d-4718-9c92-e1cc67e1e1fb · outbound

This paper cites Partial VAE for hybrid recommender system.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Partial VAE for hybrid recommender system

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation a52c7870-7fb5-4867-af01-5c68cacf35f0 · outbound

This paper cites EDDI : Efficient dynamic discovery of high-value information with partial vae.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model EDDI : Efficient dynamic discovery of high-value information with partial vae

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation e39dbe33-7c7c-43d6-a51b-4d2606080be7 · outbound

This paper cites Information-based objective functions for active data selection.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Information-based objective functions for active data selection

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation a139dc78-dc91-4d76-9ca7-e461c3455a0e · outbound

This paper cites Pointing the way: active collaborative filtering.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Pointing the way: active collaborative filtering

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 603cf5fb-051c-4699-8312-9ece8af34497 · outbound

This paper cites Employing EM and pool-based active learning for text classification.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Employing EM and pool-based active learning for text classification

Reference 31

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raw_fallback, observed 2026-08-14T13:47:03.350074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.358633Z digest=sha256:30a3772c1832e0c83eaaa74b6ca2c74d884a3574e8d28b57a0893118e115b685

Observation 8c7fb373-c293-46d4-8693-6f8451ae272f · outbound

This paper cites Active feature-value acquisition for classifier induction.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Active feature-value acquisition for classifier induction

Reference 32

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raw_fallback, observed 2026-08-14T13:47:03.325236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.364793Z digest=sha256:c339521c787958bb8571ea1bd4c7dd9a92ff81760166e0325c4c7b49681e7401

Observation d9848dc6-f447-4977-944f-7c64787cbaba · outbound

This paper cites An expected utility approach to active feature-value acquisition.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model An expected utility approach to active feature-value acquisition

Reference 33

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raw_fallback, observed 2026-08-14T13:47:03.302769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.372218Z digest=sha256:b960aa4634d52a83369faf0218943ac20fbbf2f15497773d647a15c3493de835

Observation 1c4903a4-b0ae-4601-8357-500feb77d86a · outbound

This paper cites Handling Incomplete Heterogeneous Data using VAEs.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Handling Incomplete Heterogeneous Data using VAEs

Reference 34

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no resolver link, observed 2026-08-14T13:47:02.377449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:47:02.377449Z digest=sha256:05fd785971a2aad028d6cc4c24d3edc1545fb8f208ce2c4886d37a6837cac7f4

Observation b33e8619-5da9-437c-b33b-1c768380832b · outbound

This paper cites Resolving cold start problem in recommendation system using demographic approach.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Resolving cold start problem in recommendation system using demographic approach

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.383899Z digest=sha256:ef5317f96539ef5fbeb54cbb9916c8425c99ebad87e94a7c02b394b2442febc3

Observation f165a934-2828-4202-86f9-da266f272e16 · outbound

This paper cites Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-14T13:47:02.391477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:47:02.391477Z digest=sha256:50624938ce5e4839b90eb4fa8b3f1aee5aa3a7b5229928e512d9de25a20a53de

Observation 196ae6cd-a2b1-468a-bc37-7554fc40796a · outbound

This paper cites Pointnet: Deep learning on point sets for 3D classification and segmentation.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Pointnet: Deep learning on point sets for 3D classification and segmentation

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:03.234484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.398999Z digest=sha256:62cc744fa8434a8a45753c9071cc5b44cadf4552dea0793d090863c3cd84733f

Observation 42793134-777b-4c9c-84d6-033a40f48f4c · outbound

This paper cites Stochastic backpropagation and approximate inference in deep generative models.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Stochastic backpropagation and approximate inference in deep generative models

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-14T13:47:03.206320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.405909Z digest=sha256:a4e01e4b2c0197643eb63052edaebebb63a6c62353a994ffccdc1543fbd04502

Observation ccd489f1-daa1-491b-91d3-ce0d870ff3a0 · outbound

This paper cites Toward optimal active learning through monte carlo estimation of error reduction.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Toward optimal active learning through monte carlo estimation of error reduction

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:03.181440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.415944Z digest=sha256:4df9740a6441fe111eb7ea78bce2e06013df5f7ef9db6a9bbd7d24eccf99b1fa

Observation 9f99d876-3eaf-49ef-b532-6c78979ee356 · outbound

This paper cites Matrix completion with queries.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Matrix completion with queries

Reference 40

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.425076Z digest=sha256:4b4c35487518f4e5c6c0210bab474d8eaac2bd3e13f5540db049359c74d8fb46

Observation e681514d-8ffd-46e3-892a-f8ab5d3c1500 · outbound

This paper cites Active feature-value acquisition.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Active feature-value acquisition

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:03.136901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.431197Z digest=sha256:6d8ef134f64d604c12a3198264edc8d54aa337189bb6a9730544e8450244ef19

Observation 70fce768-26bc-4c0f-8ae2-e78228675e65 · outbound

This paper cites Methods and metrics for cold-start recommendations.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Methods and metrics for cold-start recommendations

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:03.116002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.437008Z digest=sha256:a795877ddf0f10e3c5c27e52a0c2bbc20b51992cacd863680b9d0091f9970273

Observation a97e2cc0-8183-447a-b602-3412115de37e · outbound

This paper cites Active learning.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Active learning

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:03.095887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.443047Z digest=sha256:23a939c334ae2bcfa1bd2b70c293f681506a97ebc9454f1a6dfad0369ec8a1ee

Observation 51278d06-2a68-4f39-b10f-4edbef4bed98 · outbound

This paper cites Joint active feature acquisition and classification with variable-size set encoding.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Joint active feature acquisition and classification with variable-size set encoding

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:03.073774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.449148Z digest=sha256:f57f2f186ba53febe2f555cccfe9b23f1eaf4f2297892b9d7f0021b62b603f01

Observation 91ca3624-5b69-4fcf-90f6-73d8cc7cad58 · outbound

This paper cites Learning structured output representation using deep conditional generative models.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Learning structured output representation using deep conditional generative models

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:03.049016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.456303Z digest=sha256:39f844d7d89e57141f82f98c8b97d9ab2191fd7f74e2f628560b94f7caea1e61

Observation dfa89074-3bdf-438e-81f9-1269bebcf4c4 · outbound

This paper cites Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:03.024460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.462736Z digest=sha256:b25df8ab821547ea65758ce750e41a03e58dd18b723a62539aaae530021d50c8

Observation 0de442aa-9388-4e00-8042-f772136f2db2 · outbound

This paper cites Active learning and search on low-rank matrices.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Active learning and search on low-rank matrices

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:02.997574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.472210Z digest=sha256:2d8e0f90675126db57efd91e7f391f58539c7beaa265eae05414acc74af1098f

Observation 63b188f8-90bd-46e5-b218-5129db7c6caf · outbound

This paper cites An efficient heuristic method for active feature acquisition and its application to protein-protein interaction prediction.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model An efficient heuristic method for active feature acquisition and its application to protein-protein interaction prediction

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:02.973383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.478055Z digest=sha256:4208f590515365bdcc2d65facb012d56dba8c3a52547268500cbf7a03873fc68

Observation 4d1a0487-34fd-44f2-97f9-dc8f3d7fae22 · outbound

This paper cites Support vector machine active learning with applications to text classification.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Support vector machine active learning with applications to text classification

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-14T13:47:02.483760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:47:02.483760Z digest=sha256:4554d1005c7163233b70b3747483bb6ad550cbe885088558b4b0a5a7cc849dd8

Observation ef7cfaa2-a805-47ae-a731-094cf08c6473 · outbound

This paper cites Intelligent information acquisition for improved clustering.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Intelligent information acquisition for improved clustering

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:02.925211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.488587Z digest=sha256:35ee79637931a6c2fc992b623938637e739d7f4bc56bfb8725e286ebfab27e2e

Observation ca6d21fc-3222-4307-8f8c-44ba6955b98a · outbound

This paper cites Graphical models, exponential families, and variational inference.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Graphical models, exponential families, and variational inference

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-14T13:47:02.493817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:47:02.493817Z digest=sha256:fd5a1da8b186c3a4ad3e8527860d9c63af70ab0e0b7e61a764ff742ddd278114

Observation dfb69ce0-9402-4ea6-a2ed-90a3ee9ab41c · outbound

This paper cites A Monte Carlo implementation of the EM algorithm and the poor man's data augmentation algorithms.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model A Monte Carlo implementation of the EM algorithm and the poor man's data augmentation algorithms

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:02.888704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.499186Z digest=sha256:87698a3eb5d5d0945597655064ff4d6ff2be96a83ede77bc9cc3d90639d2116b

Observation 03530642-ba91-46d2-b81e-e663059472d9 · outbound

This paper cites Ice-breaking: mitigating cold-start recommendation problem by rating comparison.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Ice-breaking: mitigating cold-start recommendation problem by rating comparison

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:02.866462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.504532Z digest=sha256:a041cc4ed811c6b848c743ddd9044e0bfaf2a9f38f41a276dc7e5bdc855d0610

Observation fa79649b-f041-4719-8d3d-b0b1359fdd4b · outbound

This paper cites Deep sets.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Deep sets

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:02.844478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.509671Z digest=sha256:9fbada91b092227761e056919b99e7def52c89570672e117d58065c64d2f9d88

Observation 638137ba-e633-49da-9032-a1a292f0c429 · outbound

This paper cites Odin: Optimal discovery of high-value information using model-based deep reinforcement learning.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Odin: Optimal discovery of high-value information using model-based deep reinforcement learning

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:02.818680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.515702Z digest=sha256:fb881d0dc31c5ac0627f866f9b62a69ab9c9b81d09bd937f8dc5d893d91114b3

Observation e1059b94-ad4c-473b-b93b-ec60a2971701 · outbound

This paper cites Advances in variational inference.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Advances in variational inference

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:02.794663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.522673Z digest=sha256:b0e991c460a686d46cd8dec9c0a58dffa8828b7d5d45141cb71e50592bdea860

Observation 1dbede25-c428-450d-93a2-34c1c563bb99 · outbound

This paper cites Generative Adversarial Active Learning.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Generative Adversarial Active Learning

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-14T13:47:02.530094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:47:02.530094Z digest=sha256:1b789564c5327866e87c4daf3e69ddc97488a0b2d9da9c47b958c6115ed1e0be

Observation 8f2edb35-c4ea-4615-915a-83cbe9255aa5 · outbound

This paper cites Combining active learning and semi-supervised learning using gaussian fields and harmonic functions.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model Combining active learning and semi-supervised learning using gaussian fields and harmonic functions

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:47:02.770744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T13:47:02.535857Z digest=sha256:972112aa291e35790ddf6483c9eec4dc4fc88e0676f9a89b1a16ebd008e17b97

Pith citing papers

No inbound Pith citation observations are available.