Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model | Paper Citation Record

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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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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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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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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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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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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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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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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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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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:47:03.779977Z

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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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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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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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Source-reported events for the cited work

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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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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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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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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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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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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

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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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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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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

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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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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:47:03.557321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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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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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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

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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 2026-08-16T06:30:59.297886+00:00.

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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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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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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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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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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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:47:03.302769Z

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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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Source-reported events for the cited work

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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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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

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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

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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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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

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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

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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

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Source-reported events for the cited work

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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

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This paper cites Active learning.

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

Reference 43

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Source-reported events for the cited work

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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

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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 2026-08-16T06:30:59.297886+00:00.

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 2026-08-16T06:30:59.297886+00:00.

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 2026-08-16T06:30:59.297886+00:00.

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 2026-08-16T06:30:59.297886+00:00.

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

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Source-reported events for the cited work

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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 2026-08-16T06:30:59.297886+00:00.

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

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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

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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

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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 2026-08-16T06:30:59.297886+00:00.

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

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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

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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

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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

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