Paper Citation Record · LEDGER

Continuous nonlinear adaptive experimental design with gradient flow

As of 15 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 1 inbound Pith citation observation for arXiv:2411.14332.

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

pith.paper-citation-record.v1
2411.14332 v2

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:23:18.466580Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-08T14:18:19.330577Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T18:41:12.099533Z

Reference resolution

56 of 56 outbound references displayed

verified exact3
verified fuzzy44
unresolved9
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e18f1732-0d29-49c5-93fd-fd073ef3d90d · outbound

This paper cites Optimal experimental design for inﬁ nite-dimensional bayesian inverse problems governed by pdes: A review.

Continuous nonlinear adaptive experimental design with gradient flow Optimal experimental design for inﬁ nite-dimensional bayesian inverse problems governed by pdes: A review

Reference 1

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Observation 2cf9a936-1569-42e5-9b29-7ce6dd8671e0 · outbound

This paper cites A-optimal design of experiments for inﬁnite-dimensional bayesian li near inverse prob- lems with regularized ℓ0-sparsiﬁcation.

Continuous nonlinear adaptive experimental design with gradient flow A-optimal design of experiments for inﬁnite-dimensional bayesian li near inverse prob- lems with regularized ℓ0-sparsiﬁcation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:21.098310Z

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Observation 4ad659e2-39de-4a55-bbd5-ec1b0eb71b05 · outbound

This paper cites A fast and scalable method for a-optimal design of experiments for inﬁnite-dimensional bayesian nonlinear inverse problems.

Continuous nonlinear adaptive experimental design with gradient flow A fast and scalable method for a-optimal design of experiments for inﬁnite-dimensional bayesian nonlinear inverse problems

Reference 3

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Observation f6759895-5daa-4465-bade-2ab25b847504 · outbound

This paper cites E ﬃcient d-optimal design of exper- iments for inﬁnite-dimensional bayesian linear inverse pr oblems.

Continuous nonlinear adaptive experimental design with gradient flow E ﬃcient d-optimal design of exper- iments for inﬁnite-dimensional bayesian linear inverse pr oblems

Reference 4

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Observation 0872e9e5-969e-41ee-93ae-6a314097766a · outbound

This paper cites Gradient ﬂows: in metric spaces and in the space of probability measures.

Continuous nonlinear adaptive experimental design with gradient flow Gradient ﬂows: in metric spaces and in the space of probability measures

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:20.947982Z

Source-reported events for the cited work

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Observation b9396e20-9f4d-490b-8356-efcb969d1846 · outbound

This paper cites Introduction to optimum design.

Continuous nonlinear adaptive experimental design with gradient flow Introduction to optimum design

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:20.908742Z

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Observation 5483e881-3020-4e9c-9121-4dcd6ce8f90f · outbound

This paper cites Gone ﬁsh- ing: Neural active learning with ﬁsher embeddings.

Continuous nonlinear adaptive experimental design with gradient flow Gone ﬁsh- ing: Neural active learning with ﬁsher embeddings

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:20.874247Z

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Observation 108221a4-e625-4dc7-a80d-6e7e5d8d3788 · outbound

This paper cites Go al-oriented optimal design of experiments for large-scale bayesian linear inve rse problems.

Continuous nonlinear adaptive experimental design with gradient flow Go al-oriented optimal design of experiments for large-scale bayesian linear inve rse problems

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:20.835348Z

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Observation 4316a945-53d9-4ad0-8246-679627b6ccf5 · outbound

This paper cites Optimal and e ﬃcient designs of experiments.

Continuous nonlinear adaptive experimental design with gradient flow Optimal and e ﬃcient designs of experiments

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:20.801620Z

Source-reported events for the cited work

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Observation a9088a92-e8c8-4256-aa96-06f14864e21a · outbound

This paper cites Active perception.

Continuous nonlinear adaptive experimental design with gradient flow Active perception

Reference 10

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Source-reported events for the cited work

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Observation 60871456-eb9b-4315-a483-a67f621fc1d8 · outbound

This paper cites Schl¨ oder.

Continuous nonlinear adaptive experimental design with gradient flow Schl¨ oder

Reference 11

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Observation de86e83f-3a11-45ee-aec3-8913e49e7836 · outbound

This paper cites Practic al considerations for optimal designs in clinical dose ﬁnding studies.

Continuous nonlinear adaptive experimental design with gradient flow Practic al considerations for optimal designs in clinical dose ﬁnding studies

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:20.686236Z

Source-reported events for the cited work

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Observation bc8f6ee3-f52f-4ac7-b44b-9bc39ac3baac · outbound

This paper cites Minimax bounds for activ e learning.

Continuous nonlinear adaptive experimental design with gradient flow Minimax bounds for activ e learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:20.640738Z

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Observation be6c2505-9b55-4647-9fbc-3b724f0fd765 · outbound

This paper cites Bayesian Ex perimental Design: A Review.

Continuous nonlinear adaptive experimental design with gradient flow Bayesian Ex perimental Design: A Review

Reference 14

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Source-reported events for the cited work

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Observation 40474129-4037-4df8-af8d-c5a3e38fa327 · outbound

This paper cites Convergence rates of active learning for maximum likelihoo d estimation.

Continuous nonlinear adaptive experimental design with gradient flow Convergence rates of active learning for maximum likelihoo d estimation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:20.560424Z

Source-reported events for the cited work

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Observation 159dcbdb-8551-4d3d-bcc7-cb04367557c0 · outbound

This paper cites Determination of a Small Elliptical Anomaly in Electrical Impedance Tomography using Minimal Measurements.

Continuous nonlinear adaptive experimental design with gradient flow Determination of a Small Elliptical Anomaly in Electrical Impedance Tomography using Minimal Measurements

Reference 16

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Source-reported events for the cited work

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Observation f8a34eac-ebfd-4f8c-9d00-d41618a560c9 · outbound

This paper cites an unresolved cited work.

Continuous nonlinear adaptive experimental design with gradient flow Unresolved cited work

Reference 17

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Source-reported events for the cited work

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Observation 60a7c539-e303-4bdb-83fb-952e8abc550b · outbound

This paper cites Optimal Design for Nonlinear Response Models.

Continuous nonlinear adaptive experimental design with gradient flow Optimal Design for Nonlinear Response Models

Reference 18

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Observation 8bcde8a9-1e71-4ee9-b765-45cf3f0c260e · outbound

This paper cites Model-oriented design of experiments , vol- ume 125.

Continuous nonlinear adaptive experimental design with gradient flow Model-oriented design of experiments , vol- ume 125

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:20.425047Z

Source-reported events for the cited work

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Observation f328921d-4112-46da-952f-21aa91889267 · outbound

This paper cites Elsevier, 2013.

Continuous nonlinear adaptive experimental design with gradient flow Elsevier, 2013

Reference 20

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Observation 3780e3ba-694f-4fff-833d-9380fa45f18f · outbound

This paper cites Figalli and F.

Continuous nonlinear adaptive experimental design with gradient flow Figalli and F

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:20.321145Z

Source-reported events for the cited work

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Observation 9ced3507-c00a-4b05-a759-89ebfdcbf301 · outbound

This paper cites A uniﬁed stochastic gradient approach to design ing bayesian-optimal experiments.

Continuous nonlinear adaptive experimental design with gradient flow A uniﬁed stochastic gradient approach to design ing bayesian-optimal experiments

Reference 22

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Observation bd4b1aba-7c78-4933-a1ed-b582e2910278 · outbound

This paper cites Deep Bayesian active learning with image data.

Continuous nonlinear adaptive experimental design with gradient flow Deep Bayesian active learning with image data

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:20.229051Z

Source-reported events for the cited work

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Observation 7c661ce9-db4c-4bfc-a756-cd107edcd5ba · outbound

This paper cites Nea r-optimal bayesian ac- tive learning with noisy observations.

Continuous nonlinear adaptive experimental design with gradient flow Nea r-optimal bayesian ac- tive learning with noisy observations

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:20.158374Z

Source-reported events for the cited work

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Observation 9f08d198-3790-4faa-9e5a-24db42113fdb · outbound

This paper cites Introduction to quantum mechanics.

Continuous nonlinear adaptive experimental design with gradient flow Introduction to quantum mechanics

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:20.121372Z

Source-reported events for the cited work

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Observation 2c3c712c-159e-4857-ab41-d232d10293e3 · outbound

This paper cites Numerical methods for e xperimental design of large-scale linear ill-posed inverse problems.

Continuous nonlinear adaptive experimental design with gradient flow Numerical methods for e xperimental design of large-scale linear ill-posed inverse problems

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:20.081451Z

Source-reported events for the cited work

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Observation 35fb06b9-bd5f-4398-b450-5762d5f0bf4f · outbound

This paper cites Numerical methods for t he design of large-scale nonlinear discrete ill-posed inverse problem s.

Continuous nonlinear adaptive experimental design with gradient flow Numerical methods for t he design of large-scale nonlinear discrete ill-posed inverse problem s

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:20.052061Z

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Observation d0aacc55-9a52-491c-9300-4ef659fd503e · outbound

This paper cites Numeri- cal methods for a-optimal designs with a sparsity constrain t for ill-posed inverse problems.

Continuous nonlinear adaptive experimental design with gradient flow Numeri- cal methods for a-optimal designs with a sparsity constrain t for ill-posed inverse problems

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:20.028747Z

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Observation a2a736c8-3e82-4dc5-8ed2-8a1ddf585e0e · outbound

This paper cites Bayesian opti- mal designs for phase i clinical trials.

Continuous nonlinear adaptive experimental design with gradient flow Bayesian opti- mal designs for phase i clinical trials

Reference 29

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Observation d1c8fccb-2e97-48fa-a136-caa735a0b2a1 · outbound

This paper cites Optimization with PDE Constraints, volume 23.

Continuous nonlinear adaptive experimental design with gradient flow Optimization with PDE Constraints, volume 23

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.956444Z

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Observation fda39d5b-022b-4785-b8bb-238356773a81 · outbound

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

Continuous nonlinear adaptive experimental design with gradient flow Bayesian Active Learning for Classification and Preference Learning

Reference 31

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Observation fa3c10bc-7ae5-40a7-abba-085194cc65f8 · outbound

This paper cites Optima l experimental design: Formulations and computations.

Continuous nonlinear adaptive experimental design with gradient flow Optima l experimental design: Formulations and computations

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.918152Z

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Observation c54819b5-9467-4da1-b712-09e140273c3b · outbound

This paper cites Simulation-based optim al bayesian ex- perimental design for nonlinear systems.

Continuous nonlinear adaptive experimental design with gradient flow Simulation-based optim al bayesian ex- perimental design for nonlinear systems

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.868845Z

Source-reported events for the cited work

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Observation 0f417f26-439f-4acc-be1e-f3ccf19c09d3 · outbound

This paper cites Gradient-based stochas tic optimization methods in bayesian experimental design.

Continuous nonlinear adaptive experimental design with gradient flow Gradient-based stochas tic optimization methods in bayesian experimental design

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.827852Z

Source-reported events for the cited work

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Observation c729561f-94f8-4232-886c-6f9b9591aef8 · outbound

This paper cites Sequential Bayesian optimal experimental design via approximate dynamic programming.

Continuous nonlinear adaptive experimental design with gradient flow Sequential Bayesian optimal experimental design via approximate dynamic programming

Reference 35

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Observation 9d214f84-af14-4dfa-84ed-deac5165f4a9 · outbound

This paper cites Batch gree dy maximization of non-submodular functions: Guarantees and applications to experimental design.

Continuous nonlinear adaptive experimental design with gradient flow Batch gree dy maximization of non-submodular functions: Guarantees and applications to experimental design

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.792800Z

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Observation ed3979d7-2314-4b1c-8a2e-cef8f9a4d3d9 · outbound

This paper cites Op timal experimental design for linear models via gradient ﬂow.

Continuous nonlinear adaptive experimental design with gradient flow Op timal experimental design for linear models via gradient ﬂow

Reference 37

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Observation 03bf3739-57f3-414c-9f2a-054ef54dc723 · outbound

This paper cites Optimal designs for mi xed continuous and binary responses with quantitative and qualitative factors.

Continuous nonlinear adaptive experimental design with gradient flow Optimal designs for mi xed continuous and binary responses with quantitative and qualitative factors

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.751455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 10e03dca-1c9b-4e29-8b19-b84e381380ca · outbound

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Continuous nonlinear adaptive experimental design with gradient flow Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:23:19.700308Z

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Observation 1becc9d9-8cce-468d-acf4-602c305f46c5 · outbound

This paper cites Kiefer and J.

Continuous nonlinear adaptive experimental design with gradient flow Kiefer and J

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.656553Z

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Observation 6f06ff49-f8a4-4b9e-8387-7b775dd4e284 · outbound

This paper cites An introduction to the mathematical th eory of inverse problems.

Continuous nonlinear adaptive experimental design with gradient flow An introduction to the mathematical th eory of inverse problems

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.608009Z

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This paper cites The implicit function theorem: history, theory, and applications.

Continuous nonlinear adaptive experimental design with gradient flow The implicit function theorem: history, theory, and applications

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.573722Z

Source-reported events for the cited work

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Observation 2770ed54-b57b-4de3-89f3-2967f6e4a4c8 · outbound

This paper cites Nonlinear Bayesian optimal experimental design using logarithmic Sobolev inequalities.

Continuous nonlinear adaptive experimental design with gradient flow Nonlinear Bayesian optimal experimental design using logarithmic Sobolev inequalities

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-08-12T15:23:18.677657Z

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Observation 23937f9f-7c43-4930-a98f-ae57cfcd935f · outbound

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Continuous nonlinear adaptive experimental design with gradient flow Unresolved cited work

Reference 44

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:23:19.505453Z

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Observation b35ca5ad-2192-42d3-89ad-d6c4c9dc237e · outbound

This paper cites Continuous-v ariable optical quantum-state tomography.

Continuous nonlinear adaptive experimental design with gradient flow Continuous-v ariable optical quantum-state tomography

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.467431Z

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Observation 01bdc154-e295-4f0e-96e4-91db476de458 · outbound

This paper cites D-optimal.

Continuous nonlinear adaptive experimental design with gradient flow D-optimal

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.407262Z

Source-reported events for the cited work

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Observation e794d50d-e4a0-46c6-aee7-ba772b7aa5f0 · outbound

This paper cites Active Learning with Expected Error Reduction.

Continuous nonlinear adaptive experimental design with gradient flow Active Learning with Expected Error Reduction

Reference 47

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Source-reported events for the cited work

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This paper cites Optimal Design of Experiments.

Continuous nonlinear adaptive experimental design with gradient flow Optimal Design of Experiments

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-12T15:23:18.392687Z

Source-reported events for the cited work

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Observation f2481dde-8503-4d92-ad99-e8fa079709b8 · outbound

This paper cites Design and analysis of computer experiments.

Continuous nonlinear adaptive experimental design with gradient flow Design and analysis of computer experiments

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.322776Z

Source-reported events for the cited work

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Observation dfcfbffc-bf59-4016-9add-44ba458e4582 · outbound

This paper cites Optimal Transport for Applied Mathematicians: Calculus of V ariations, PDEs, and Modeling, volume 87.

Continuous nonlinear adaptive experimental design with gradient flow Optimal Transport for Applied Mathematicians: Calculus of V ariations, PDEs, and Modeling, volume 87

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.283837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b6f3f878-35db-44e4-beb9-ed966bd3b6a4 · outbound

This paper cites Bayesian sequential optimal experimental design for linear regression with reinforcement learning.

Continuous nonlinear adaptive experimental design with gradient flow Bayesian sequential optimal experimental design for linear regression with reinforcement learning

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.223868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f0239af1-f029-4923-97dd-3dd038ea4fe5 · outbound

This paper cites Active Learning for Convolutional Neural Networks: A Core-Set Approach.

Continuous nonlinear adaptive experimental design with gradient flow Active Learning for Convolutional Neural Networks: A Core-Set Approach

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-12T15:23:18.427291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f96063b-abc5-49e5-9ae4-605ab3f26971 · outbound

This paper cites Active learning literature survey.

Continuous nonlinear adaptive experimental design with gradient flow Active learning literature survey

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-12T15:23:18.439177Z

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Observation f979f9c4-af64-487d-a06a-e3cf4194d03d · outbound

This paper cites Inverse problem theory and methods for model parameter esti - mation.

Continuous nonlinear adaptive experimental design with gradient flow Inverse problem theory and methods for model parameter esti - mation

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.156777Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8c5d3e75-1cac-4987-8e5a-10a7fc200124 · outbound

This paper cites The sequential generation of d-optimum experimental designs.

Continuous nonlinear adaptive experimental design with gradient flow The sequential generation of d-optimum experimental designs

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.114342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 01d8940b-dd07-4784-b30b-262f3a95748a · outbound

This paper cites Mastering quantum mechanics: essentials, theory, and appl i- cations.

Continuous nonlinear adaptive experimental design with gradient flow Mastering quantum mechanics: essentials, theory, and appl i- cations

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:23:19.069825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

Observation a109ed88-5f16-4168-9ad8-d18bf875e3c1 · inbound

Beyond Expected Information Gain: Stable Bayesian Optimal Experimental Design with Integral Probability Metrics and Plug-and-Play Extensions cites this paper.

Beyond Expected Information Gain: Stable Bayesian Optimal Experimental Design with Integral Probability Metrics and Plug-and-Play Extensions Continuous nonlinear adaptive experimental design with gradient flow

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:41:12.106807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.