Paper Citation Record · LEDGER

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints

As of 19 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2507.04929.

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

pith.paper-citation-record.v1
2507.04929 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:42:35.760858Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

43 of 43 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c720e496-273b-4aec-891f-7710a921dc0d · outbound

This paper cites A survey on active learning and human-in-the-loop deep learning for medical image analysis.Medical image analysis, 71:102062, 2021.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints A survey on active learning and human-in-the-loop deep learning for medical image analysis.Medical image analysis, 71:102062, 2021

Reference 1

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Observation 4a6dfd13-ba88-4bc8-a806-a3a9abdd7fde · outbound

This paper cites Active learning for improved semi-supervised semantic segmentation in satellite images.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Active learning for improved semi-supervised semantic segmentation in satellite images

Reference 2

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Observation a8d74639-0d06-4b2d-8808-c202f4382d33 · outbound

This paper cites Active learning for structural reliability: Survey, general framework and benchmark.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Active learning for structural reliability: Survey, general framework and benchmark

Reference 3

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This paper cites Deep Bayesian active learning with image data.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Deep Bayesian active learning with image data

Reference 4

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Observation d723624f-bf87-46ee-aeb2-ae02f6c022fd · outbound

This paper cites Bayesian neural networks and density networks.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Bayesian neural networks and density networks

Reference 5

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Observation 3d5a5be6-5d2d-45cc-9b6e-8d804a8b49cb · outbound

This paper cites Bayesian learning for neural networks , volume 118.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Bayesian learning for neural networks , volume 118

Reference 6

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Observation 1d8da37d-8ca5-4cc8-92dd-6f6b51062dcc · outbound

This paper cites Deep Bayesian active learning-to-rank with relative annotation for estimation of ulcerative colitis severity.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Deep Bayesian active learning-to-rank with relative annotation for estimation of ulcerative colitis severity

Reference 7

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Observation 204ba340-c3d3-409a-9c68-5ee721528afb · outbound

This paper cites Active learning with convolutional neural networks for hyperspectral image classification using a new Bayesian approach.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Active learning with convolutional neural networks for hyperspectral image classification using a new Bayesian approach

Reference 8

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Observation f39d41b2-58ac-4189-9e09-67fae8f5113e · outbound

This paper cites Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study

Reference 9

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Source-reported events for the cited work

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Observation 21e1d8f5-77fc-4c33-9cff-fe384f13fdb5 · outbound

This paper cites Challenges in Markov chain Monte Carlo for Bayesian neural networks.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Challenges in Markov chain Monte Carlo for Bayesian neural networks

Reference 10

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Observation 8fbdee78-05b3-433f-9a1c-337c13af30f2 · outbound

This paper cites A complete recipe for stochastic gradient MCMC.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints A complete recipe for stochastic gradient MCMC

Reference 11

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Source-reported events for the cited work

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Observation cf36c415-6b8d-4d42-8570-17a0c3cd5c9e · outbound

This paper cites Bayesian model comparison and backprop nets.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Bayesian model comparison and backprop nets

Reference 12

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Observation 665e2081-03a8-4c6b-8292-543d28247ea8 · outbound

This paper cites Dropout as a Bayesian approximation: Representing model uncertainty in deep learning.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Dropout as a Bayesian approximation: Representing model uncertainty in deep learning

Reference 13

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Observation c2bce39a-15a8-41c1-90bd-692228e9dd87 · outbound

This paper cites Deep Bayesian Active Learning, A Brief Survey on Recent Advances.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Deep Bayesian Active Learning, A Brief Survey on Recent Advances

Reference 14

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Observation e2859f89-e0a0-4b15-af1f-2c709352a3f2 · outbound

This paper cites A survey on Bayesian deep learning.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints A survey on Bayesian deep learning

Reference 15

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Observation 2e06ad73-57af-4e23-a11e-c91cf4ff5136 · outbound

This paper cites A review of uncertainty quantification in deep learning: Techniques, applications and challenges.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints A review of uncertainty quantification in deep learning: Techniques, applications and challenges

Reference 16

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Observation 94d410a7-655d-41ba-b2d5-9b387a49a2ec · outbound

This paper cites Uncertainty in deep learning.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Uncertainty in deep learning

Reference 17

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Observation f7925346-5782-41e4-9caa-f5c05422f756 · outbound

This paper cites A mathematical theory of communication.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints A mathematical theory of communication

Reference 18

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This paper cites Elementary applied statistics.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Elementary applied statistics

Reference 19

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Observation 74df95dd-035c-4c4e-92c7-ed08dcd5eff3 · outbound

This paper cites Batchbald: Efficient and diverse batch acquisition for deep Bayesian active learning.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Batchbald: Efficient and diverse batch acquisition for deep Bayesian active learning

Reference 20

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Observation 286c30ec-1dd9-449d-b806-1a9677690fe9 · outbound

This paper cites Speeding Up BatchBALD: A k-BALD Family of Approximations for Active Learning.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Speeding Up BatchBALD: A k-BALD Family of Approximations for Active Learning

Reference 21

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Observation f210c43a-630d-45c7-a559-eaea35024291 · outbound

This paper cites Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds

Reference 22

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This paper cites Bayesian batch active learning as sparse subset approximation.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Bayesian batch active learning as sparse subset approximation

Reference 23

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Observation 73dee689-0639-401e-8c71-78fb735b7a98 · outbound

This paper cites Stochastic Batch Acquisition: A Simple Baseline for Deep Active Learning.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Stochastic Batch Acquisition: A Simple Baseline for Deep Active Learning

Reference 24

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This paper cites Active learning for cost-sensitive classification.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Active learning for cost-sensitive classification

Reference 25

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Observation d49a6e37-58cc-44f5-b14f-acc3c0153132 · outbound

This paper cites Learning cost-sensitive active classifiers.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Learning cost-sensitive active classifiers

Reference 26

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Observation ce7fe50b-d844-4244-8b0d-f1ac62ec2cc4 · outbound

This paper cites Optimised probabilistic active learning (OPAL) for fast, non-myopic, cost-sensitive active classification.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Optimised probabilistic active learning (OPAL) for fast, non-myopic, cost-sensitive active classification

Reference 27

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Observation e0433ee7-49b2-468e-8684-5bc300de1cee · outbound

This paper cites Batch multi-fidelity active learning with budget constraints.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Batch multi-fidelity active learning with budget constraints

Reference 28

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Observation cd959167-f754-4668-b796-6a64e1fc0602 · outbound

This paper cites Aid: A benchmark data set for performance evaluation of aerial scene classification.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Aid: A benchmark data set for performance evaluation of aerial scene classification

Reference 29

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Observation 716440ab-4941-4d1a-8256-c6ef13343ab2 · outbound

This paper cites xView: Objects in Context in Overhead Imagery.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints xView: Objects in Context in Overhead Imagery

Reference 30

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Observation a6de35e7-4f7f-4921-a1d9-1960f2a36525 · outbound

This paper cites Dota: A large-scale dataset for object detection in aerial images.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Dota: A large-scale dataset for object detection in aerial images

Reference 31

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This paper cites SPAGRI-AI: Smart precision agriculture dataset of aerial images at different heights for crop and weed detection using super-resolution.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints SPAGRI-AI: Smart precision agriculture dataset of aerial images at different heights for crop and weed detection using super-resolution

Reference 32

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Observation 9fffe195-291c-4e7b-8bf4-fc469a0b12c8 · outbound

This paper cites Estimating building energy efficiency from street view imagery, aerial imagery, and land surface temperature data.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Estimating building energy efficiency from street view imagery, aerial imagery, and land surface temperature data

Reference 33

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Observation d47c070f-0765-4df2-84b5-1811068975a3 · outbound

This paper cites Review of 50 years of EU energy efficiency policies for buildings.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Review of 50 years of EU energy efficiency policies for buildings

Reference 34

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Observation d5965152-752c-4b20-b71c-8b9387d7a2a7 · outbound

This paper cites The relationship be- tween operational energy demand and embodied energy in Dutch residential buildings.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints The relationship be- tween operational energy demand and embodied energy in Dutch residential buildings

Reference 35

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Observation c40ad079-53db-4eba-b1c7-d4fedf6a557c · outbound

This paper cites PDOK - Publieke Dienstverlening Op de Kaart.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints PDOK - Publieke Dienstverlening Op de Kaart

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:35.974412Z

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Observation f9722cf5-f9de-4ece-a3f4-216b1efd7210 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints DINOv2: Learning Robust Visual Features without Supervision

Reference 37

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This paper cites Understanding architecture age and style through deep learning.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Understanding architecture age and style through deep learning

Reference 38

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Observation 107d69e5-1175-4dd0-a344-a080ca7c8eb0 · outbound

This paper cites Bayesian learning via stochastic gradient Langevin dynamics.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Bayesian learning via stochastic gradient Langevin dynamics

Reference 39

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Observation 0e6cb7c3-628f-4894-8022-ae5b88d1f592 · outbound

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ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Stochastic gradient hamiltonian monte carlo

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:35.934877Z

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Observation 67f285c1-9996-4a57-be40-54aa225831cb · outbound

This paper cites Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning

Reference 41

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ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints 3D BAG viewer

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:35.921804Z

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Observation dc5c49a8-8756-4554-9b5a-4a35e210b890 · outbound

This paper cites R VO - Rijksdienst voor Ondernemend Nederland.

ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints R VO - Rijksdienst voor Ondernemend Nederland

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:35.909015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.