Paper Citation Record · LEDGER

Distance-informed Neural Processes

As of 21 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 2 inbound Pith citation observations for arXiv:2508.18903.

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

pith.paper-citation-record.v1
2508.18903 v1

Coverage vector

measured 69 of 69 reference resolution

Typed states for the displayed outbound observations.

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measured 71 of 71 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T11:04:17.549829Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T02:16:26.916376Z

Reference resolution

69 of 69 outbound references displayed

verified exact2
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External citation measurements

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Outbound references

Observation 40cb5d6b-c55d-4e59-955a-1b81009e6df0 · outbound

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

Distance-informed Neural Processes A review of uncertainty quantification in deep learning: Techniques, applications and challenges

Reference 1

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Observation ac4e568f-3203-4f6b-872e-f5e40323a2ea · outbound

This paper cites Invertible residual networks.

Distance-informed Neural Processes Invertible residual networks

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:10:10.234279Z

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Observation 565864ac-e243-462e-9760-0fc1782fbe37 · outbound

This paper cites Weight uncertainty in neural network.

Distance-informed Neural Processes Weight uncertainty in neural network

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:10:10.217639Z

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Observation be91805a-80d4-4d6a-9127-6b000ab59f55 · outbound

This paper cites Neural Photo Editing with Introspective Adversarial Networks.

Distance-informed Neural Processes Neural Photo Editing with Introspective Adversarial Networks

Reference 4

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Observation a1d04d24-cea8-4800-8cde-af2f0be6767e · outbound

This paper cites Deep learning in computer vision: A critical review of emerging techniques and application scenarios.

Distance-informed Neural Processes Deep learning in computer vision: A critical review of emerging techniques and application scenarios

Reference 5

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Observation fb5c625d-3509-4e3b-a12e-354cae9e5fae · outbound

This paper cites Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

Distance-informed Neural Processes Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)

Reference 6

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Observation ac7cf1f3-96b9-4e04-9947-a01279da6bc3 · outbound

This paper cites Predicting chemical parameters of river water quality from bioindicator data.

Distance-informed Neural Processes Predicting chemical parameters of river water quality from bioindicator data

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:10:10.178042Z

Source-reported events for the cited work

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Observation 70924ecd-09ae-410b-9d6e-0e7a31a3ff0c · outbound

This paper cites Meta-learning stationary stochastic process prediction with convolutional neural processes.

Distance-informed Neural Processes Meta-learning stationary stochastic process prediction with convolutional neural processes

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:10:10.159091Z

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Observation 02bf9396-1815-4fdf-bcea-76eb2e0e00ad · outbound

This paper cites An introduction to deep reinforcement learning.

Distance-informed Neural Processes An introduction to deep reinforcement learning

Reference 9

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Observation 7343f5c8-6e0b-41db-b251-7daabcc1feee · outbound

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

Distance-informed Neural Processes Dropout as a bayesian approximation: Representing model uncertainty in deep learning

Reference 10

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Observation b31b3f80-639e-44e3-8628-67f7a67e5615 · outbound

This paper cites Conditional neural processes.

Distance-informed Neural Processes Conditional neural processes

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:10:10.111506Z

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Observation 635ab363-40b8-41da-a493-d59eda472981 · outbound

This paper cites Neural Processes.

Distance-informed Neural Processes Neural Processes

Reference 12

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Observation af87aac1-5aef-4aac-aedc-e495d4fb5640 · outbound

This paper cites Function contrastive learning of transferable meta-representations.

Distance-informed Neural Processes Function contrastive learning of transferable meta-representations

Reference 13

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Observation 1b2f9377-a100-4b5c-89aa-949532f94328 · outbound

This paper cites Convolutional Conditional Neural Processes.

Distance-informed Neural Processes Convolutional Conditional Neural Processes

Reference 14

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Observation e027dead-7a52-4935-b444-eb23fb8b39db · outbound

This paper cites Practical variational inference for neural networks.Advances in neural information processing systems, 24, 2011.

Distance-informed Neural Processes Practical variational inference for neural networks.Advances in neural information processing systems, 24, 2011

Reference 15

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Observation 653d2c1b-c4e5-4028-8027-81884d8bb0d0 · outbound

This paper cites Improved training of wasserstein gans.

Distance-informed Neural Processes Improved training of wasserstein gans

Reference 16

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Observation dacefcd9-511e-49bc-99cc-6ddb23b28606 · outbound

This paper cites On calibration of modern neural networks.

Distance-informed Neural Processes On calibration of modern neural networks

Reference 17

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Observation 8e54306f-dee4-40ee-b5d3-72983d973819 · outbound

This paper cites Delving deep into rectifiers: Surpassing human-level performance on imagenet classification.

Distance-informed Neural Processes Delving deep into rectifiers: Surpassing human-level performance on imagenet classification

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:10:10.040091Z

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Observation 84743644-c89c-4326-a05f-c1325da33a79 · outbound

This paper cites Robust Learning with Jacobian Regularization.

Distance-informed Neural Processes Robust Learning with Jacobian Regularization

Reference 19

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Observation 2b9c2b36-5e52-4067-802c-9b0aa556f44d · outbound

This paper cites Meta-learning in neural networks: A survey.

Distance-informed Neural Processes Meta-learning in neural networks: A survey

Reference 20

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Observation 70dcb92f-147f-4a63-b2ac-db8bf2db5cac · outbound

This paper cites i-RevNet: Deep Invertible Networks.

Distance-informed Neural Processes i-RevNet: Deep Invertible Networks

Reference 21

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This paper cites Transformers are rnns: Fast autoregressive transformers with linear attention.

Distance-informed Neural Processes Transformers are rnns: Fast autoregressive transformers with linear attention

Reference 22

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Observation b1f48777-8bdf-4521-bbbb-cb837b361534 · outbound

This paper cites What uncertainties do we need in bayesian deep learning for computer vision? Advances in neural information processing systems, 30, 2017.

Distance-informed Neural Processes What uncertainties do we need in bayesian deep learning for computer vision? Advances in neural information processing systems, 30, 2017

Reference 23

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Observation 911a0ab4-7e71-4ed1-a317-d7ac9cfc888a · outbound

This paper cites Multi-task learning using uncertainty to weigh losses for scene geometry and semantics.

Distance-informed Neural Processes Multi-task learning using uncertainty to weigh losses for scene geometry and semantics

Reference 24

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Observation d3c351a4-368c-4e03-9e93-4ef0dc720a92 · outbound

This paper cites Attentive Neural Processes.

Distance-informed Neural Processes Attentive Neural Processes

Reference 25

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Observation 0ad9f453-c2a1-4d94-9af9-e8b17e535a35 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Distance-informed Neural Processes Adam: A Method for Stochastic Optimization

Reference 26

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This paper cites An introduction to variational autoencoders.

Distance-informed Neural Processes An introduction to variational autoencoders

Reference 27

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Observation 7b7c299e-d9a2-4fd4-adbc-db8f06527c8c · outbound

This paper cites Toward the optimal preconditioned eigensolver: Locally optimal block preconditioned conjugate gradient method.

Distance-informed Neural Processes Toward the optimal preconditioned eigensolver: Locally optimal block preconditioned conjugate gradient method

Reference 28

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Observation 762a90a5-384b-467e-a639-d2af5d1e7777 · outbound

This paper cites Learning multiple layers of features from tiny images.

Distance-informed Neural Processes Learning multiple layers of features from tiny images

Reference 29

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This paper cites Accurate uncertainties for deep learning using calibrated regression.

Distance-informed Neural Processes Accurate uncertainties for deep learning using calibrated regression

Reference 30

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This paper cites Simple and scalable predictive uncertainty estimation using deep ensembles.

Distance-informed Neural Processes Simple and scalable predictive uncertainty estimation using deep ensembles

Reference 31

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This paper cites Tiny imagenet visual recognition challenge.

Distance-informed Neural Processes Tiny imagenet visual recognition challenge

Reference 32

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This paper cites Bootstrapping neural processes.

Distance-informed Neural Processes Bootstrapping neural processes

Reference 33

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Observation f7b8678b-46fd-4acb-803e-756c8d7a1b77 · outbound

This paper cites The ecological role of volterra’s equations.

Distance-informed Neural Processes The ecological role of volterra’s equations

Reference 34

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Observation 314cbf5f-7be5-4a03-ba7f-cc65aac3b6d1 · outbound

This paper cites Simple and principled uncertainty estimation with deterministic deep learning via distance awareness.

Distance-informed Neural Processes Simple and principled uncertainty estimation with deterministic deep learning via distance awareness

Reference 35

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This paper cites The functional neural process.

Distance-informed Neural Processes The functional neural process

Reference 36

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Observation 7cbc0338-e0b5-4653-80fc-0314fc817228 · outbound

This paper cites Rectifier nonlinearities improve neural network acoustic models.

Distance-informed Neural Processes Rectifier nonlinearities improve neural network acoustic models

Reference 37

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Observation b631c2a2-6783-4263-b87c-ccbe67c7bf00 · outbound

This paper cites Spectral Normalization for Generative Adversarial Networks.

Distance-informed Neural Processes Spectral Normalization for Generative Adversarial Networks

Reference 38

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This paper cites Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling.

Distance-informed Neural Processes Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling

Reference 39

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This paper cites Stochastic differential equations.

Distance-informed Neural Processes Stochastic differential equations

Reference 40

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This paper cites A survey of the usages of deep learning for natural language processing.

Distance-informed Neural Processes A survey of the usages of deep learning for natural language processing

Reference 41

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This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

Distance-informed Neural Processes PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 42

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This paper cites Fubini’s theorem and tonelli’s theorem.

Distance-informed Neural Processes Fubini’s theorem and tonelli’s theorem

Reference 43

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Observation 1ebaf7b4-83c5-4841-bd76-2e0c1b087f95 · outbound

This paper cites Convolutional neural networks applied to house numbers digit classification.

Distance-informed Neural Processes Convolutional neural networks applied to house numbers digit classification

Reference 44

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Observation 59d2c88b-8f13-4d04-9b41-5c5896a3281c · outbound

This paper cites A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference.

Distance-informed Neural Processes A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference

Reference 45

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This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Distance-informed Neural Processes Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 46

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Distance-informed Neural Processes Sparse gaussian processes using pseudo-inputs

Reference 47

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Distance-informed Neural Processes Multi-target regression via input space expansion: treating targets as inputs

Reference 48

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Distance-informed Neural Processes A block orthogonalization procedure with constant synchronization requirements

Reference 49

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This paper cites Exploiting inferential structure in neural processes.

Distance-informed Neural Processes Exploiting inferential structure in neural processes

Reference 50

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Observation ab187c5e-8814-40de-9b90-4acccccc3275 · outbound

This paper cites Sparse sinkhorn attention.

Distance-informed Neural Processes Sparse sinkhorn attention

Reference 51

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Observation dc1d1447-0866-42a5-be02-16861acc0dd0 · outbound

This paper cites Variational learning of inducing variables in sparse gaussian processes.

Distance-informed Neural Processes Variational learning of inducing variables in sparse gaussian processes

Reference 52

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This paper cites On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty.

Distance-informed Neural Processes On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty

Reference 53

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Observation 7b5d7203-42cd-4f0f-8175-27cfafa74896 · outbound

This paper cites Uncertainty estimation using a single deep deterministic neural network.

Distance-informed Neural Processes Uncertainty estimation using a single deep deterministic neural network

Reference 54

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Observation a8f59007-f291-4f02-bb05-bcaea7027033 · outbound

This paper cites Attention is all you need.

Distance-informed Neural Processes Attention is all you need

Reference 55

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This paper cites Gaussian latent representations for uncertainty estimation using mahalanobis distance in deep classifiers.

Distance-informed Neural Processes Gaussian latent representations for uncertainty estimation using mahalanobis distance in deep classifiers

Reference 56

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Observation dec8983c-6a67-4c2f-a8b0-3749a9aec775 · outbound

This paper cites Probabilistic Embeddings for Frozen Vision-Language Models: Uncertainty Quantification with Gaussian Process Latent Variable Models.

Distance-informed Neural Processes Probabilistic Embeddings for Frozen Vision-Language Models: Uncertainty Quantification with Gaussian Process Latent Variable Models

Reference 57

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This paper cites Integrating visual and semantic similarity using hierarchies for image retrieval.

Distance-informed Neural Processes Integrating visual and semantic similarity using hierarchies for image retrieval

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:10:09.629496Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation be4d3bdb-e3c7-4098-ad9c-adedbdde24f9 · outbound

This paper cites Locally weighted projection regression: An o (n) algorithm for incremental real time learning in high dimensional space.

Distance-informed Neural Processes Locally weighted projection regression: An o (n) algorithm for incremental real time learning in high dimensional space

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:10:09.613528Z

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Observation 0021a57a-9aed-4be0-9904-2fa6b3b4dc72 · outbound

This paper cites Bridge the Inference Gaps of Neural Processes via Expectation Maximization.

Distance-informed Neural Processes Bridge the Inference Gaps of Neural Processes via Expectation Maximization

Reference 60

Resolution: verified exact; local_arxiv, observed 2026-08-05T16:10:09.208359Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3c08b131-bbfa-410b-ae70-27197972d78a · outbound

This paper cites Doubly stochastic variational inference for neural processes with hierarchical latent variables.

Distance-informed Neural Processes Doubly stochastic variational inference for neural processes with hierarchical latent variables

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:10:09.597777Z

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Observation 577ab1c1-c1d0-4828-aa0f-f9adaf865e6d · outbound

This paper cites Learning expressive meta-representations with mixture of expert neural processes.

Distance-informed Neural Processes Learning expressive meta-representations with mixture of expert neural processes

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:10:09.582363Z

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Observation a8459448-f78a-4cd4-a548-b359d460423f · outbound

This paper cites Stochastic modelling for systems biology.

Distance-informed Neural Processes Stochastic modelling for systems biology

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:10:09.561667Z

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Observation 9f16756b-dff5-4ba8-98f7-cf5068a9d164 · outbound

This paper cites MIT press Cambridge, MA, 2006.

Distance-informed Neural Processes MIT press Cambridge, MA, 2006

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-05T16:10:09.121776Z

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Unavailable: canonical work link unavailable.

Observation 5a840652-b349-42ac-be93-77d8196c2154 · outbound

This paper cites Deep kernel learning.

Distance-informed Neural Processes Deep kernel learning

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:10:09.535166Z

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Observation e31a82e2-7663-437a-a02b-e187e1bbf063 · outbound

This paper cites Spectral Norm Regularization for Improving the Generalizability of Deep Learning.

Distance-informed Neural Processes Spectral Norm Regularization for Improving the Generalizability of Deep Learning

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-05T16:10:09.130484Z

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Observation 617a0c59-cb5f-4335-ae26-27372ba1aa75 · outbound

This paper cites Rank-n-contrast: Learning continuous representations for regression.

Distance-informed Neural Processes Rank-n-contrast: Learning continuous representations for regression

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:10:09.514650Z

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Observation 84d0bfcf-0509-43d5-9677-39365947b0b3 · outbound

This paper cites , N}; that is, px1:N (y1:N ) = pxπ(1:N ) (yπ(1:N )) (14).

Distance-informed Neural Processes , N}; that is, px1:N (y1:N ) = pxπ(1:N ) (yπ(1:N )) (14)

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:10:09.497135Z

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Observation 1446361f-f210-45e6-acf6-f06927cc8e6b · outbound

This paper cites , yM } of the outputs must be recoverable by integrating out the remaining variables from the joint distribution px1:N (y1:N ).

Distance-informed Neural Processes , yM } of the outputs must be recoverable by integrating out the remaining variables from the joint distribution px1:N (y1:N )

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:10:09.481205Z

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Pith citing papers

Observation 81f990df-7933-4480-93f5-a7fc82e60ebc · inbound

Spectral Transformer Neural Processes cites this paper.

Spectral Transformer Neural Processes Distance-informed Neural Processes

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:41:34.789544Z

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Observation 4d06f26e-576b-424a-85c0-075a093bf034 · inbound

APIC: Amortized Physics-Informed Calibration using Neural Processes cites this paper.

APIC: Amortized Physics-Informed Calibration using Neural Processes Distance-informed Neural Processes

Reference 30

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T02:16:26.917939Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.