Paper Citation Record · LEDGER

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs

As of 16 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:1908.09744.

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

pith.paper-citation-record.v1
1908.09744 v4

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:08:47.439543Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

47 of 47 outbound references displayed

verified exact2
verified fuzzy35
unresolved10
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2cf87994-d556-48bf-80ce-d3bf07fff3ee · outbound

This paper cites Winbugs-a bayesian modelling framework: concepts, structure, and extensibility.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Winbugs-a bayesian modelling framework: concepts, structure, and extensibility

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:49.310442Z

Source-reported events for the cited work

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Observation 86f4d291-a679-499f-922f-3f6944c87e2c · outbound

This paper cites Stan: A probabilistic programming language.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Stan: A probabilistic programming language

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:49.289334Z

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Observation 8ab9a103-9751-497b-bf14-6b301370837e · outbound

This paper cites Simple, distributed, and accelerated probabilistic programming.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Simple, distributed, and accelerated probabilistic programming

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:49.262827Z

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Observation fc6baeb9-259a-4157-8c59-03788afe38f0 · outbound

This paper cites Pyro: Deep Universal Probabilistic Programming.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Pyro: Deep Universal Probabilistic Programming

Reference 4

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Source-reported events for the cited work

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Observation 48560a30-b781-4e68-91ee-fa866effb621 · outbound

This paper cites Auto-Encoding Variational Bayes.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Auto-Encoding Variational Bayes

Reference 5

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Source-reported events for the cited work

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Observation 8b05bbac-5f9d-4b47-a8d7-dc783dbb7d5a · outbound

This paper cites A tutorial on hidden markov models and selected applications in speech recognition.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs A tutorial on hidden markov models and selected applications in speech recognition

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:49.245517Z

Source-reported events for the cited work

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Observation 83e33688-99b3-4f90-ad13-0309bc5c2f13 · outbound

This paper cites Particle Markov chain monte carlo methods.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Particle Markov chain monte carlo methods

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:49.226385Z

Source-reported events for the cited work

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Observation 32fcabf8-3ed4-4081-9241-17c5d166a63f · outbound

This paper cites Mcmc using hamiltonian dynamics.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Mcmc using hamiltonian dynamics

Reference 8

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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 91eeee61-7ba2-42f8-a4ca-8b476a9cd2c2 · outbound

This paper cites Automatic differentiation variational inference.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Automatic differentiation variational inference

Reference 9

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Source-reported events for the cited work

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Observation a7f4231e-2897-43e4-ac42-fe9912c49a34 · outbound

This paper cites Approx- imate inference for deep latent gaussian mixtures.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Approx- imate inference for deep latent gaussian mixtures

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:49.174324Z

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 e9025d5b-f417-40a3-a40b-3ba381ac82b8 · outbound

This paper cites Markov chain monte carlo and variational inference: Bridging the gap.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Markov chain monte carlo and variational inference: Bridging the gap

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:49.157589Z

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 2d1e2665-3c0a-47bd-b708-d43353bb07d5 · outbound

This paper cites The Variational Gaussian Process.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs The Variational Gaussian Process

Reference 12

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Source-reported events for the cited work

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Observation 97c2ee22-fe18-49ea-8c76-ae314921e545 · outbound

This paper cites A new approach to probabilistic programming inference.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs A new approach to probabilistic programming inference

Reference 13

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Source-reported events for the cited work

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Observation 831cf315-ec2a-496b-8933-358f7c31ea36 · outbound

This paper cites Turing: a language for ﬂexible probabilistic inference.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Turing: a language for ﬂexible probabilistic inference

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:49.123463Z

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 8fe748e9-1b7c-4179-9c99-ea1977dd65c0 · outbound

This paper cites A general framework for the parametrization of hierarchical models.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs A general framework for the parametrization of hierarchical models

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:49.105092Z

Source-reported events for the cited work

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Observation 8cbfc440-c1b3-4569-8486-da2bace97824 · outbound

This paper cites Neutra- lizing bad geometry in hamiltonian monte carlo using neural transport.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Neutra- lizing bad geometry in hamiltonian monte carlo using neural transport

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:49.085380Z

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 3feec916-d112-407a-bf65-87fe2990c195 · outbound

This paper cites Neural network renormaliza- tion group.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Neural network renormaliza- tion group

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:49.067977Z

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 94b46c9e-3fe8-45c5-bd3a-98c8e410dd67 · outbound

This paper cites Transport map accelerated Markov chain Monte Carlo.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Transport map accelerated Markov chain Monte Carlo

Reference 18

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Source-reported events for the cited work

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Observation 9a32a376-1b84-4256-976b-4d5562f120e3 · outbound

This paper cites Variational infer- ence with normalizing ﬂows.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Variational infer- ence with normalizing ﬂows

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:49.049662Z

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 dcfde0aa-5265-4f0e-8f4f-2bc5a3fbe5eb · outbound

This paper cites Continuous-time ﬂows for efﬁcient inference and density estimation, 2018.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Continuous-time ﬂows for efﬁcient inference and density estimation, 2018

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:49.032935Z

Source-reported events for the cited work

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Observation 5ea69632-aa7d-47c6-bdab-8359e74d47d0 · outbound

This paper cites Generative adversarial nets.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Generative adversarial nets

Reference 21

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Source-reported events for the cited work

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

Observation ad35fb0a-70f3-4c57-ba60-d94f264c7ec5 · outbound

This paper cites Variational Inference using Implicit Distributions.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Variational Inference using Implicit Distributions

Reference 22

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Source-reported events for the cited work

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Observation 94326789-6efb-4d98-a11f-25316d5f6957 · outbound

This paper cites Unbiased im- plicit variational inference.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Unbiased im- plicit variational inference

Reference 23

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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 07c0d969-972b-40c8-a94e-b63a7c22852d · outbound

This paper cites Semi-Implicit Variational Inference.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Semi-Implicit Variational Inference

Reference 24

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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 1400b346-7f66-4133-b859-44bbfcb462c8 · outbound

This paper cites Learning deep latent gaussian mod- els with markov chain monte carlo.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Learning deep latent gaussian mod- els with markov chain monte carlo

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:48.976250Z

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 b0ec4b98-bc82-470f-846d-957bd27ec226 · outbound

This paper cites Learning to Draw Samples with Amortized Stein Variational Gradient Descent.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Learning to Draw Samples with Amortized Stein Variational Gradient Descent

Reference 26

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Source-reported events for the cited work

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Observation 1c6ddf12-6dcf-4a34-83b5-36d7da273e83 · outbound

This paper cites Inference Suboptimality in Variational Autoencoders.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Inference Suboptimality in Variational Autoencoders

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-14T11:08:46.839043Z

Source-reported events for the cited work

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Observation 7d1625a6-5e89-419d-9008-f13e71b199fe · outbound

This paper cites A contrastive di- vergence for combining variational inference and mcmc.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs A contrastive di- vergence for combining variational inference and mcmc

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:48.958005Z

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 90539709-1111-4686-934e-4e2cb6cbba51 · outbound

This paper cites Bayesian learning via stochastic gradient langevin dynamics.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Bayesian learning via stochastic gradient langevin dynamics

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:48.935764Z

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 1021e34a-028b-426f-97e0-edadf6db407f · outbound

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

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Preconditioned stochastic gradient langevin dynamics for deep neural networks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:48.916058Z

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 7ddafd66-1ab6-42d7-a4e0-a95e45368338 · outbound

This paper cites High-order stochastic gradient thermostats for bayesian learning of deep models.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs High-order stochastic gradient thermostats for bayesian learning of deep models

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:48.879670Z

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Observation 52f8e861-4801-4bd1-80bc-dfaa9a0d88ef · outbound

This paper cites Adageo: Adaptive geometric learning for optimization and sampling.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Adageo: Adaptive geometric learning for optimization and sampling

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:48.861284Z

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 a76ef65f-336b-4df0-81f3-cbe5f9479051 · outbound

This paper cites Stochastic Gradient MCMC with Repulsive Forces.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Stochastic Gradient MCMC with Repulsive Forces

Reference 33

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Source-reported events for the cited work

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Observation b1c45f6e-9c21-4a39-8300-769eb95d7279 · outbound

This paper cites Stochastic gradient descent as approximate bayesian in- ference.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Stochastic gradient descent as approximate bayesian in- ference

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:48.826435Z

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 cb609506-a655-4a0a-9a28-d14e2f9acdc1 · outbound

This paper cites Stein variational gradient descent: A general purpose bayesian inference algorithm.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Stein variational gradient descent: A general purpose bayesian inference algorithm

Reference 35

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Observation de642067-8cb9-46e5-a2a6-24d9dd5299ab · outbound

This paper cites Early stopping as nonparametric variational inference.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Early stopping as nonparametric variational inference

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:48.624321Z

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 51dc61f8-0f5c-458e-9b28-4db5da2645d7 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Adam: A Method for Stochastic Optimization

Reference 37

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Source-reported events for the cited work

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Observation 88859f73-21a9-49dd-8c19-8d055ca0d21e · outbound

This paper cites Forward and reverse gradient-based hyperparameter optimization.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Forward and reverse gradient-based hyperparameter optimization

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:48.582929Z

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 ef2d625c-35a4-487f-b542-9cdb030b628f · outbound

This paper cites Coupled variational bayes via optimization embedding.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Coupled variational bayes via optimization embedding

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:48.535436Z

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 ae37e56c-ab6e-4c04-9441-712a68d7abd5 · outbound

This paper cites Implicit deep latent variable models for text generation.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Implicit deep latent variable models for text generation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:48.440537Z

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 504308f2-1d04-448e-b8dd-eb72cc6c80b6 · outbound

This paper cites Automatic differentiation in pytorch.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Automatic differentiation in pytorch

Reference 41

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f2d2358-e2d6-4b41-a6de-319c36af84a5 · outbound

This paper cites Fundamentals of Kalman ﬁltering: a practical approach.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Fundamentals of Kalman ﬁltering: a practical approach

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:48.286783Z

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 f5ffec4b-da55-4876-ab73-9e5e123d8f46 · outbound

This paper cites Strictly proper scoring rules, prediction, and estimation.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Strictly proper scoring rules, prediction, and estimation

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-14T11:08:47.393960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f92cba4e-a9f2-49d8-a959-86b10931bc3e · outbound

This paper cites Atmospheric carbon dioxide record from mauna loa.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Atmospheric carbon dioxide record from mauna loa

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:48.163974Z

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 8e95a3f5-4c81-4eff-ba9c-73ce90ee8485 · outbound

This paper cites Inﬂuence dia- grams.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Inﬂuence dia- grams

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:48.057639Z

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 62b075fa-4038-4ba0-9ac4-c7eb2661c890 · outbound

This paper cites Shachter.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Shachter

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:47.995387Z

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 c94a7cd4-9542-4455-87f9-8b8cb854eb3d · outbound

This paper cites A spectral ap- proach to gradient estimation for implicit distributions.

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs A spectral ap- proach to gradient estimation for implicit distributions

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:08:47.949084Z

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.

Pith citing papers

No inbound Pith citation observations are available.