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Paper Citation Record · LEDGER

Molecular Machine Learning Using Euler Characteristic Transforms

As of 8 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:2507.03474.

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

pith.paper-citation-record.v1
2507.03474 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:12:51.197575Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T13:46:37.365525Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:37:37.167951Z

Reference resolution

35 of 35 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 02164d4c-90ee-4ed8-9661-a8d1d5b8aff2 · outbound

This paper cites Measuring hidden phenotype: quantifying the shape of barley seeds using the euler characteristic transform.

Molecular Machine Learning Using Euler Characteristic Transforms Measuring hidden phenotype: quantifying the shape of barley seeds using the euler characteristic transform

Reference 1

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Observation eb22a5bc-590a-410c-8440-1d2678589d8a · outbound

This paper cites Geometric deep learning on molecular representations.

Molecular Machine Learning Using Euler Characteristic Transforms Geometric deep learning on molecular representations

Reference 2

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Observation 5651c3c8-4d7e-4898-8fe0-08adfb86536f · outbound

This paper cites Evaluating molecular representations in machine learning models for drug response prediction and interpretability.

Molecular Machine Learning Using Euler Characteristic Transforms Evaluating molecular representations in machine learning models for drug response prediction and interpretability

Reference 3

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Observation d73ce2d6-26f6-466a-8629-20552d21723b · outbound

This paper cites A review on machine learning approaches and trends in drug discovery.

Molecular Machine Learning Using Euler Characteristic Transforms A review on machine learning approaches and trends in drug discovery

Reference 4

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Observation 60540f06-257b-4c8d-aa1a-e8cbaa38fb76 · outbound

This paper cites XGBoost: A scalable tree boosting system.

Molecular Machine Learning Using Euler Characteristic Transforms XGBoost: A scalable tree boosting system

Reference 5

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Observation 3fdb88c7-4b5c-4571-adba-3e9287cbd980 · outbound

This paper cites Molecules and medicine.

Molecular Machine Learning Using Euler Characteristic Transforms Molecules and medicine

Reference 6

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Observation 587cd232-31bc-448b-babd-5f7ea383eba7 · outbound

This paper cites Predicting Clinical Outcomes in Glioblastoma: An Application of Topological and Functional Data Analysis.

Molecular Machine Learning Using Euler Characteristic Transforms Predicting Clinical Outcomes in Glioblastoma: An Application of Topological and Functional Data Analysis

Reference 7

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Observation c3248741-b029-40ca-ac6c-b4b71f1c4c90 · outbound

This paper cites Molecular representations in AI-driven drug discovery: a review and practical guide.

Molecular Machine Learning Using Euler Characteristic Transforms Molecular representations in AI-driven drug discovery: a review and practical guide

Reference 8

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Observation 95d7f4fc-504c-4d40-8144-944b99ce548a · outbound

This paper cites Artificial intelligence in drug discovery: applications and techniques.

Molecular Machine Learning Using Euler Characteristic Transforms Artificial intelligence in drug discovery: applications and techniques

Reference 9

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Observation 30a226e1-e391-474f-a277-491393f14127 · outbound

This paper cites A systematic study of key elements underlying molecular property prediction.

Molecular Machine Learning Using Euler Characteristic Transforms A systematic study of key elements underlying molecular property prediction

Reference 10

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Observation f93e45cf-c3eb-49a4-8356-780b039df88b · outbound

This paper cites Drug discovery: A historical perspective.

Molecular Machine Learning Using Euler Characteristic Transforms Drug discovery: A historical perspective

Reference 11

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Observation 0fe42d07-2388-4c9a-b44c-60bbf04245e9 · outbound

This paper cites Computational topology: an introduction.

Molecular Machine Learning Using Euler Characteristic Transforms Computational topology: an introduction

Reference 12

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Observation 97f8899c-816e-437b-9001-185d726a852d · outbound

This paper cites Hamilton.

Molecular Machine Learning Using Euler Characteristic Transforms Hamilton

Reference 13

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This paper cites Algebraic topology.

Molecular Machine Learning Using Euler Characteristic Transforms Algebraic topology

Reference 14

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Observation e67082db-87ce-4284-9303-a128b6c2fc10 · outbound

This paper cites Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models.

Molecular Machine Learning Using Euler Characteristic Transforms Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models

Reference 15

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Observation 5df9955d-79fe-4866-90c6-c0023b8b96da · outbound

This paper cites The weighted Euler curve transform for shape and image analysis.

Molecular Machine Learning Using Euler Characteristic Transforms The weighted Euler curve transform for shape and image analysis

Reference 16

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Observation 3d8fe6d2-2254-4ebc-b58a-92984902e4ad · outbound

This paper cites Bronstein, and Daniel Cremers.

Molecular Machine Learning Using Euler Characteristic Transforms Bronstein, and Daniel Cremers

Reference 17

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Observation 79e99b8e-9351-447f-9728-3b018acb1e34 · outbound

This paper cites A fast and scalable computational topology framework for the Euler characteristic.

Molecular Machine Learning Using Euler Characteristic Transforms A fast and scalable computational topology framework for the Euler characteristic

Reference 18

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Observation 5eb152ca-fa7f-440f-8c14-407e12697121 · outbound

This paper cites The Euler characteristic of a category.

Molecular Machine Learning Using Euler Characteristic Transforms The Euler characteristic of a category

Reference 19

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This paper cites Extracting insights from the shape of complex data using topology.

Molecular Machine Learning Using Euler Characteristic Transforms Extracting insights from the shape of complex data using topology

Reference 20

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Observation d37cf5e6-c4bb-41dd-b503-310f93c7ac8c · outbound

This paper cites alvaDesc: A tool to calculate and analyze molecular descriptors and fingerprints.

Molecular Machine Learning Using Euler Characteristic Transforms alvaDesc: A tool to calculate and analyze molecular descriptors and fingerprints

Reference 21

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Observation de01e561-6c94-4f34-91a5-107cee8c70f0 · outbound

This paper cites An invitation to the Euler characteristic transform.

Molecular Machine Learning Using Euler Characteristic Transforms An invitation to the Euler characteristic transform

Reference 22

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Observation c677f1de-e372-45d3-878e-6a4a3419aeea · outbound

This paper cites Elements of algebraic topology.

Molecular Machine Learning Using Euler Characteristic Transforms Elements of algebraic topology

Reference 23

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Observation c5bdbbf6-5439-444b-89e1-6afb1cb54d65 · outbound

This paper cites A critical look at the evaluation of GNNs under heterophily: Are we really making progress?.

Molecular Machine Learning Using Euler Characteristic Transforms A critical look at the evaluation of GNNs under heterophily: Are we really making progress?

Reference 24

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This paper cites Topology meets machine learning: An introduction using the Euler characteristic transform.

Molecular Machine Learning Using Euler Characteristic Transforms Topology meets machine learning: An introduction using the Euler characteristic transform

Reference 25

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This paper cites Differentiable Euler characteristic transforms for shape classification.

Molecular Machine Learning Using Euler Characteristic Transforms Differentiable Euler characteristic transforms for shape classification

Reference 26

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This paper cites The topology of molecular representations and its influence on machine learning performance.

Molecular Machine Learning Using Euler Characteristic Transforms The topology of molecular representations and its influence on machine learning performance

Reference 27

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Observation 126b1505-9dc3-41e7-91f0-99a56bead548 · outbound

This paper cites Topological analysis of molecular dynamics simulations using the euler characteristic.

Molecular Machine Learning Using Euler Characteristic Transforms Topological analysis of molecular dynamics simulations using the euler characteristic

Reference 28

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Molecular Machine Learning Using Euler Characteristic Transforms Unresolved cited work

Reference 29

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This paper cites Exposing the limitations of molecular machine learning with activity cliffs.

Molecular Machine Learning Using Euler Characteristic Transforms Exposing the limitations of molecular machine learning with activity cliffs

Reference 30

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Molecular Machine Learning Using Euler Characteristic Transforms Unresolved cited work

Reference 31

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This paper cites Applications of deep learning in molecule generation and molecular property prediction.

Molecular Machine Learning Using Euler Characteristic Transforms Applications of deep learning in molecule generation and molecular property prediction

Reference 32

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This paper cites A review of molecular representation in the age of machine learning.

Molecular Machine Learning Using Euler Characteristic Transforms A review of molecular representation in the age of machine learning

Reference 33

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Observation ab992053-229b-4a9e-85e2-d56ac17bd168 · outbound

This paper cites Pushing the boundaries of molecular representation for drug discovery with the graph attention mechanism.

Molecular Machine Learning Using Euler Characteristic Transforms Pushing the boundaries of molecular representation for drug discovery with the graph attention mechanism

Reference 34

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Observation 0023da14-2d0f-45de-9ea4-90fbc9efbf09 · outbound

This paper cites Graph neural networks: A review of methods and applications.

Molecular Machine Learning Using Euler Characteristic Transforms Graph neural networks: A review of methods and applications

Reference 35

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Pith citing papers

Observation 39d2eebd-9705-436f-a4c1-7d5ad97253d9 · inbound

Encoding the Euler Characteristic Transform cites this paper.

Encoding the Euler Characteristic Transform Molecular Machine Learning Using Euler Characteristic Transforms

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T13:46:37.365525Z digest=sha256:4103042dc4185a858fab76321d8f0d6427be5232b235f5acdd301f517bd5b828