CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization | Paper Citation Record

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This paper cites Turner, Eric Nalisnick, and José Miguel Hernández-Lobato.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Turner, Eric Nalisnick, and José Miguel Hernández-Lobato

Reference 1

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Observation 1b569a59-f688-4fa2-ad12-308b2c4814ff · outbound

This paper cites Adaptive Conformal Prediction by Reweighting Nonconformity Score.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Adaptive Conformal Prediction by Reweighting Nonconformity Score

Reference 2

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Observation b1b88628-b396-46f5-bb93-57a8c0159e53 · outbound

This paper cites Conformal pid control for time series prediction.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal pid control for time series prediction

Reference 3

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Observation 7dce510f-9c7a-4beb-b1d9-b834ca96b406 · outbound

This paper cites Conformal prediction: A gentle introduction.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal prediction: A gentle introduction

Reference 4

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Observation a8fabd4f-e5aa-4b8e-a45e-5e5cbc5ba6ce · outbound

This paper cites Theoretical Foundations of Conformal Prediction.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Theoretical Foundations of Conformal Prediction

Reference 5

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Observation 564bc8a0-bca9-4d8d-bc1c-78f628443496 · outbound

This paper cites Conformal risk control.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal risk control

Reference 6

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Observation f87d48fd-272f-4f07-9d08-66397ece798f · outbound

This paper cites Online conformal prediction with decaying step sizes.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Online conformal prediction with decaying step sizes

Reference 7

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Observation ba19ad65-bb47-4a9f-a8bf-d73ae3abd88c · outbound

This paper cites Frame averaging for equivariant shape space learning.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Frame averaging for equivariant shape space learning

Reference 8

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Observation 8fb1ae37-7269-4507-a7ef-150bc7ca4470 · outbound

This paper cites Conformal prediction beyond exchangeability.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal prediction beyond exchangeability

Reference 9

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Observation eea7d01d-b311-4cf9-8e04-6dcedfeb74f2 · outbound

This paper cites Varshney.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Varshney

Reference 10

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Observation b8c37690-db65-4469-a099-7208b1422cdd · outbound

This paper cites Varshney, Lav R.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Varshney, Lav R

Reference 11

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Observation e2d118c2-88c1-4491-8774-73e4fc187b99 · outbound

This paper cites The need for uncertainty quantification in machine-assisted medical decision making.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization The need for uncertainty quantification in machine-assisted medical decision making

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:36.166499Z

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Observation dd194b16-a3b1-4164-9639-c84ef3727131 · outbound

This paper cites B-spline cnns on lie groups.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization B-spline cnns on lie groups

Reference 13

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Observation dbbaff6d-90df-47d0-893e-9698519785db · outbound

This paper cites Probabilistic symmetries and invariant neural networks.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Probabilistic symmetries and invariant neural networks

Reference 14

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Observation 559ee8d3-40f8-4729-940a-50030962b093 · outbound

This paper cites Does equivariance matter at scale?.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Does equivariance matter at scale?

Reference 15

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Observation 4211aa2b-53e1-41a4-bdb7-d21c2edfb31c · outbound

This paper cites Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

Reference 16

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Observation 9ce3c31d-9e1f-407d-88ac-8ef97b5dc975 · outbound

This paper cites Knowing what you know: Valid and validated confidence sets in multiclass and multilabel prediction.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Knowing what you know: Valid and validated confidence sets in multiclass and multilabel prediction

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:35.580475Z

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Observation b6385c79-cba4-4f7b-b58f-95f4035b3de3 · outbound

This paper cites Group equivariant convolutional networks.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Group equivariant convolutional networks

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:35.398585Z

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Observation cb1824e0-062c-41ff-b166-f8354ad84792 · outbound

This paper cites Gauge equivariant convolutional networks and the icosahedral CNN.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Gauge equivariant convolutional networks and the icosahedral CNN

Reference 19

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Observation ea98d84e-586f-4f0a-8033-4ce544ceeec1 · outbound

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CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Unresolved cited work

Reference 20

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Observation 96500fb2-e0b4-41ac-be95-1c09f264d7c4 · outbound

This paper cites Malliaros, Yoshua Bengio, and David Rolnick.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Malliaros, Yoshua Bengio, and David Rolnick

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:34.796279Z

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Observation 7d535c16-4d93-432d-b795-38a3fcfaa435 · outbound

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CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Unresolved cited work

Reference 22

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Observation 6369fb4f-dea3-4e5b-bf03-f620c4c8d634 · outbound

This paper cites Generalizing convolutional neural networks for equivariance to lie groups on arbitrary continuous data.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Generalizing convolutional neural networks for equivariance to lie groups on arbitrary continuous data

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:34.475230Z

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Observation 2641d597-b9f6-408d-a640-073b42871732 · outbound

This paper cites A practical method for constructing equivariant multilayer perceptrons for arbitrary matrix groups.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization A practical method for constructing equivariant multilayer perceptrons for arbitrary matrix groups

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:34.270948Z

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Observation b7f1a37a-1c8d-4429-96a8-3cab5f994d91 · outbound

This paper cites Guest editorial special issue on geometric deep learning in medical imaging.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Guest editorial special issue on geometric deep learning in medical imaging

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:34.064329Z

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Observation 8cc204e9-8f61-4773-b333-34713d72d8f7 · outbound

This paper cites A survey of uncertainty in deep neural networks.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization A survey of uncertainty in deep neural networks

Reference 26

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Observation 960a7e0b-8a04-4e21-97f5-6730c754f2a5 · outbound

This paper cites Cand \`e s.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Cand \`e s

Reference 27

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Observation af4671aa-7cc8-4213-aed9-4a88538db9ae · outbound

This paper cites Localized conformal prediction: A generalized inference framework for conformal prediction.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Localized conformal prediction: A generalized inference framework for conformal prediction

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:33.648784Z

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Observation 982bc5a8-9d57-4738-8e0c-9f8335eb3b1a · outbound

This paper cites Batch Multivalid Conformal Prediction.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Batch Multivalid Conformal Prediction

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:33.409248Z

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Observation 73382903-1b10-4f12-9161-6c20ca5d640f · outbound

This paper cites Equivariance with learned canonicalization functions.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Equivariance with learned canonicalization functions

Reference 30

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Observation a73d6d84-9d4f-4e8b-9347-7e44269f6c66 · outbound

This paper cites idecode: In-distribution equivariance for conformal out-of-distribution detection.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization idecode: In-distribution equivariance for conformal out-of-distribution detection

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:33.053700Z

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Observation cc793487-877b-436b-afac-f9fefc32eb56 · outbound

This paper cites Comprehensive review of neural network-based prediction intervals and new advances.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Comprehensive review of neural network-based prediction intervals and new advances

Reference 32

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Observation 8310a8e0-eb4c-4314-9aed-6bc4c1df86a3 · outbound

This paper cites Learning probabilistic symmetrization for architecture agnostic equivariance.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Learning probabilistic symmetrization for architecture agnostic equivariance

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:32.821725Z

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Observation fdc0d41f-bbdc-405d-9529-b77ce2394c91 · outbound

This paper cites Wilds: A benchmark of in-the-wild distribution shifts.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Wilds: A benchmark of in-the-wild distribution shifts

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:32.717077Z

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Observation 3e98072e-45b0-4d54-8ab0-78e971d16e92 · outbound

This paper cites Empirical frequentist coverage of deep learning uncertainty quantification procedures.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Empirical frequentist coverage of deep learning uncertainty quantification procedures

Reference 35

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Observation 3fc4ca45-6b99-41e7-85ac-d78bf6c30343 · outbound

This paper cites Forecasting and uncertainty: A survey.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Forecasting and uncertainty: A survey

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:32.508112Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d42b1c8b-4967-4461-a64e-20a596798071 · outbound

This paper cites Equivariant adaptation of large pretrained models.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Equivariant adaptation of large pretrained models

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:32.296727Z

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Observation d8e5daa2-a351-442d-b4b5-4c245c7ef974 · outbound

This paper cites Can you trust your model's uncertainty? evaluating predictive uncertainty under dataset shift.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Can you trust your model's uncertainty? evaluating predictive uncertainty under dataset shift

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:32.021027Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 876baef4-0f3d-4695-a5f2-675876067c80 · outbound

This paper cites Uncertain about uncertainty: How qualitative expressions of forecaster confidence impact decision-making with uncertainty visualizations.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Uncertain about uncertainty: How qualitative expressions of forecaster confidence impact decision-making with uncertainty visualizations

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:31.900147Z

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Observation 8654e9d6-2a86-4623-bb53-77b33c4a935a · outbound

This paper cites Improved canonicalization for model agnostic equivariance.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Improved canonicalization for model agnostic equivariance

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:31.802989Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a19b95d4-2ef7-4668-a799-3da3a8648bb6 · outbound

This paper cites Conformal prediction with Neural Networks.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal prediction with Neural Networks

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:31.656863Z

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Observation 9ea1bc28-b6f5-4dfd-a7b2-1f821f79c41c · outbound

This paper cites Distribution-free uncertainty quantification for classification under label shift.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Distribution-free uncertainty quantification for classification under label shift

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:31.403884Z

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Observation daad0664-4606-4f71-b276-d934ef36a523 · outbound

This paper cites Conformal validity guarantees exist for any data distribution (and how to find them).

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal validity guarantees exist for any data distribution (and how to find them)

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:31.200005Z

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Observation 8efbf8af-5a79-4b53-8418-91e82d552b3e · outbound

This paper cites Conformal time series decomposition with component-wise exchangeability.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal time series decomposition with component-wise exchangeability

Reference 44

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9fabf6bd-3c1e-4af8-a4de-9476fca7eff1 · outbound

This paper cites Smith, Ishan Misra, Aditya Grover, and Yaron Lipman.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Smith, Ishan Misra, Aditya Grover, and Yaron Lipman

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:30.768724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c13ce386-aa68-4d75-a804-e510de30c16f · outbound

This paper cites an unresolved cited work.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Unresolved cited work

Reference 46

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:48:30.645266Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 810079fc-9553-4cab-a6ef-21ba5a712a10 · outbound

This paper cites Dataset shift in machine learning.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Dataset shift in machine learning

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:30.524476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b781d472-dc7d-4838-b191-e81c9848adfb · outbound

This paper cites With Malice Towards None : Assessing Uncertainty via Equalized Coverage.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization With Malice Towards None : Assessing Uncertainty via Equalized Coverage

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:30.405277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7b881fa1-3d19-46ce-b9ec-ff804cce5978 · outbound

This paper cites an unresolved cited work.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:48:30.281795Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a8348428-7e4f-44df-a38d-0982c4a3c711 · outbound

This paper cites Romero and Suhas Lohit.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Romero and Suhas Lohit

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:30.133775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5c83bdae-08ed-4e3f-9271-ed14fb157f62 · outbound

This paper cites Clifford group equivariant neural networks.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Clifford group equivariant neural networks

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:30.021713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation dd3ec5b6-4587-4c27-a27b-2b3bc4b94b65 · outbound

This paper cites Least ambiguous set-valued classifiers with bounded error levels.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Least ambiguous set-valued classifiers with bounded error levels

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:29.885740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c54a16ee-4244-4868-9576-47d51553c79b · outbound

This paper cites Conformal Prediction using Conditional Histograms.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal Prediction using Conditional Histograms

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:29.781465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6cad7883-e453-4283-b404-5491392a7915 · outbound

This paper cites Conformal prediction using conditional histograms.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal prediction using conditional histograms

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:29.660769Z

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Observation 406bfd9e-a68f-481b-a7d8-40eee16e1cb4 · outbound

This paper cites A tutorial on conformal prediction.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization A tutorial on conformal prediction

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:29.530173Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8e7de2a0-2108-4c08-b182-dd4cc47bd545 · outbound

This paper cites Conformal prediction under covariate shift.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Conformal prediction under covariate shift

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:29.332718Z

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Observation a6761123-dfce-454d-be73-ed7fda880c29 · outbound

This paper cites Adaptive bounding box uncertainties via two-step conformal prediction.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Adaptive bounding box uncertainties via two-step conformal prediction

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:29.170013Z

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Observation 35b229be-a3ad-4479-8b5b-6fb36830d6d6 · outbound

This paper cites Combination of inductive mondrian conformal predictors.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Combination of inductive mondrian conformal predictors

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:29.020644Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 960b2b50-8554-4d26-bbd4-f846f28cf477 · outbound

This paper cites an unresolved cited work.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:48:28.866078Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1f721928-f412-4ef9-ac94-d3c8a5bd676b · outbound

This paper cites Probing Equivariance and Symmetry Breaking in Convolutional Networks.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Probing Equivariance and Symmetry Breaking in Convolutional Networks

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-06T23:48:27.282258Z

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Observation d4052ab8-6025-4c24-9005-44dba26648d2 · outbound

This paper cites van der Linden, Alejandro García-Castellanos, Sharvaree Vadgama, Thijs P.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization van der Linden, Alejandro García-Castellanos, Sharvaree Vadgama, Thijs P

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:28.676775Z

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Observation db5ff9aa-b026-49ce-9167-a3b0255f9750 · outbound

This paper cites Algorithmic learning in a random world.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Algorithmic learning in a random world

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-06T23:48:27.497258Z

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Unavailable: canonical work link unavailable.

Observation 8d6c6006-4c3d-4a27-a31c-c5bd6a736cda · outbound

This paper cites Sarma, Michael M.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Sarma, Michael M

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:28.534222Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9bc7b78a-06fc-4887-a6e6-753d37296335 · outbound

This paper cites General e(2)-equivariant steerable cnns.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization General e(2)-equivariant steerable cnns

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:28.355991Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4ccf8097-3ba6-4edc-adb4-d01d4ee580ce · outbound

This paper cites Can llms express their uncertainty? an empirical evaluation of confidence elicitation in llms.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Can llms express their uncertainty? an empirical evaluation of confidence elicitation in llms

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:28.199199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b3ca30df-92d8-4259-9e89-5a4168cd9b26 · outbound

This paper cites Adaptive conformal predictions for time series.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Adaptive conformal predictions for time series

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:28.003561Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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