Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T20:14:54.556974Z
Paper Citation Record · LEDGER
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction
As of 23 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2501.09103.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
53 of 53 outbound references displayed
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- verified fuzzy16
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 73db602a-e420-4afd-a126-88cad26056df · outbound
This paper cites Geometric deep learning on molecular repre- sentations.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Geometric deep learning on molecular repre- sentations
Reference 1
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Observation 410cfad2-99c2-4e01-b2b4-c9e972de313b · outbound
This paper cites Schoenholz, Patrick F.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Schoenholz, Patrick F
Reference 2
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Source-reported events for the cited work
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Observation b0b472d9-9bf2-4c85-b62d-04355ddeb542 · outbound
This paper cites Analyzing learned molecular representations for property prediction.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Analyzing learned molecular representations for property prediction
Reference 3
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Observation 5a3626c4-e12b-418b-a175-2ba999868ec2 · outbound
This paper cites Pushing the boundaries of molecular representation for drug discovery with the graph attention mechanism.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Pushing the boundaries of molecular representation for drug discovery with the graph attention mechanism
Reference 4
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Observation e80df15f-0069-4257-b974-7cd6db8eb9fd · outbound
This paper cites Spherical message passing for 3D molecular graphs.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Spherical message passing for 3D molecular graphs
Reference 5
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Observation 831a1df5-cab2-48d0-af75-19af9e59615f · outbound
This paper cites an unresolved cited work.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Unresolved cited work
Reference 6
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Source-reported events for the cited work
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Observation b0d3465d-aae1-4ca3-a39f-b7fbfe832806 · outbound
This paper cites E(n) equivariant graph neural networks,.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction E(n) equivariant graph neural networks,
Reference 7
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 424c92bb-c460-4bb2-80bf-00b8bb889900 · outbound
This paper cites SMILES-BERT: Large scale unsupervised pre-training for molecular property prediction.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction SMILES-BERT: Large scale unsupervised pre-training for molecular property prediction
Reference 8
- Resolution
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Observation bc7c3f52-25d3-432e-9ba7-2b8130402b14 · outbound
This paper cites SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery
Reference 9
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Observation 1e708c81-a11b-4e62-886d-1f4aefa699bc · outbound
This paper cites RoBERTa: A robustly optimized BERT pretraining approach,.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction RoBERTa: A robustly optimized BERT pretraining approach,
Reference 10
- Resolution
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Observation 19359063-225a-458c-926d-ce062c342f86 · outbound
This paper cites ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction
Reference 11
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e0ecb1c2-2b30-438a-8c9c-a7160c2d4947 · outbound
This paper cites Large-scale chemical language representations capture molecular structure and properties.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Large-scale chemical language representations capture molecular structure and properties
Reference 12
- Resolution
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Observation 0768a674-9bd1-4338-b842-0898b9ffcb63 · outbound
This paper cites Chuang, Laura M.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Chuang, Laura M
Reference 13
- Resolution
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Observation de13e517-ba49-41be-b9aa-07d869af003b · outbound
This paper cites Fundamentals of Medicinal Chemistry.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Fundamentals of Medicinal Chemistry
Reference 14
- Resolution
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Observation d60ed8c7-5da5-45cf-8ccb-d57bf149f901 · outbound
This paper cites Matched molecular pair analysis in drug discovery: Methods and recent applications.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Matched molecular pair analysis in drug discovery: Methods and recent applications
Reference 15
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Observation 0949cfb4-41e3-430f-961e-b8842b8c33d6 · outbound
This paper cites A systematic study of key elements underlying molecular property prediction.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction A systematic study of key elements underlying molecular property prediction
Reference 16
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Observation 72bac261-5c22-4474-85db-6e239b9f58d5 · outbound
This paper cites an unresolved cited work.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Unresolved cited work
Reference 17
- Resolution
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Observation c7f64bab-bc2a-4585-8f0d-4c092e9d93a6 · outbound
This paper cites MaskMol: Knowledge-guided molecular image pre-training framework for activity cliffs with pixel masking.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction MaskMol: Knowledge-guided molecular image pre-training framework for activity cliffs with pixel masking
Reference 18
- Resolution
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Observation 208f7b71-4191-4d24-a7a0-f6fe08421bfd · outbound
This paper cites Prediction of activity cliffs on the basis of images using convolutional neural networks.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Prediction of activity cliffs on the basis of images using convolutional neural networks
Reference 19
- Resolution
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Observation 7fcb63ef-b145-4d4c-a677-c6f7caf9b374 · outbound
This paper cites Prediction of activity cliffs using condensed graphs of reaction representations, descriptor recombination, support vector machine classification, and support vector regression.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Prediction of activity cliffs using condensed graphs of reaction representations, descriptor recombination, support vector machine classification, and support vector regression
Reference 21
- Resolution
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Observation 4a9e33e9-1405-4a94-b1a7-3dc19df16e78 · outbound
This paper cites Exploring qsar models for activity- cliff prediction.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Exploring qsar models for activity- cliff prediction
Reference 22
- Resolution
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Source-reported events for the cited work
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Observation 2ebd71b3-2a0d-4391-a038-6c4b886f2d19 · outbound
This paper cites Exposing the limitations of molecular machine learning with activity cliffs.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Exposing the limitations of molecular machine learning with activity cliffs
Reference 23
- Resolution
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Observation 82eab794-8301-4d9f-a34b-82c14849e39f · outbound
This paper cites Metric Learning: A Survey.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Metric Learning: A Survey
Reference 24
- Resolution
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Observation a6d1a6a4-17e2-498c-9e56-6e705be53683 · outbound
This paper cites Learning to Rank for Information Retrieval.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Learning to Rank for Information Retrieval
Reference 25
- Resolution
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Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Unresolved cited work
Reference 26
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Observation f3a110ed-ac09-408a-8700-f80af4925ff2 · outbound
This paper cites Few-shot learning for low-data drug discovery.Journal of Chemical Information and Modeling, 63(1):27–42, 2023.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Few-shot learning for low-data drug discovery.Journal of Chemical Information and Modeling, 63(1):27–42, 2023
Reference 27
- Resolution
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Observation e0d03210-c644-4832-8813-9397de3778f1 · outbound
This paper cites FS-Mol: A few-shot learning dataset of molecules.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction FS-Mol: A few-shot learning dataset of molecules
Reference 28
- Resolution
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Source-reported events for the cited work
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Observation 8905b531-6995-4825-8cee-582c13a15fd8 · outbound
This paper cites Implicitly Guided Design with PropEn: Match your Data to Follow the Gradient.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Implicitly Guided Design with PropEn: Match your Data to Follow the Gradient
Reference 29
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Observation 446927ab-8908-42e7-b487-d3729230b1c5 · outbound
This paper cites Pappu, and Vijay Pande.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Pappu, and Vijay Pande
Reference 30
- Resolution
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Observation 226c3061-c377-41b3-84e8-4c10b7e5c974 · outbound
This paper cites Twin neural network regression is a semi- supervised regression algorithm.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Twin neural network regression is a semi- supervised regression algorithm
Reference 31
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Observation e690746e-71f5-49e5-b509-daacdda5c3c8 · outbound
This paper cites Pairwise Difference Learning for Classification.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Pairwise Difference Learning for Classification
Reference 32
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Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Burrill, Enrique R
Reference 33
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Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Twin neural network regression
Reference 34
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Observation 17eba87d-5566-4734-b2e7-d891f3a0713b · outbound
This paper cites Finding the most potent compounds using active learning on molecular pairs.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Finding the most potent compounds using active learning on molecular pairs
Reference 35
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Observation da2c350b-4255-4b12-81dc-121b033057c7 · outbound
This paper cites Random forests.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Random forests
Reference 36
- Resolution
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Source-reported events for the cited work
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Observation 12b0ad0f-4135-4381-936f-591a0ceeb570 · outbound
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Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction XGBoost: A scalable tree boosting system
Reference 37
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This paper cites DeepDelta: predicting ADMET improve- ments of molecular derivatives with deep learning.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction DeepDelta: predicting ADMET improve- ments of molecular derivatives with deep learning
Reference 38
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Observation 7d94659d-7917-49ad-87f0-34017f812dd6 · outbound
This paper cites RDKit: Open-source cheminformatics software, 2016.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction RDKit: Open-source cheminformatics software, 2016
Reference 39
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Observation ffc1bd65-894a-408f-b58d-b6e9f9b6f6c6 · outbound
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Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Strategies for pre-training graph neural networks
Reference 40
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Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Prin- cipal neighbourhood aggregation for graph nets
Reference 41
- Resolution
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Observation 5cac2628-d746-454d-9027-a18955377b8b · outbound
This paper cites Extended-connectivity fingerprints.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Extended-connectivity fingerprints
Reference 42
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This paper cites Williams, Carl Underkoffler, Ryan Pederson, Narbe Mardirossian, Ian Watson, and John Parkhill.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Williams, Carl Underkoffler, Ryan Pederson, Narbe Mardirossian, Ian Watson, and John Parkhill
Reference 43
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 52f72154-c646-4773-aa44-d47be769e04a · outbound
This paper cites Gotta be SAFE: A New Framework for Molecular Design.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Gotta be SAFE: A New Framework for Molecular Design
Reference 44
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Observation b589eeba-c994-44c0-a029-28d50d2c7c4e · outbound
This paper cites Uni-Mol: A universal 3D molecular representation learning framework.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Uni-Mol: A universal 3D molecular representation learning framework
Reference 45
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 0364801f-a34f-4fdf-a9f2-b576843afc4a · outbound
This paper cites Systematic benchmark of substructure search in molecular graphs - from Ullmann to VF2.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Systematic benchmark of substructure search in molecular graphs - from Ullmann to VF2
Reference 46
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 036cde0d-4044-4ece-9ec4-1e0b4c89a511 · outbound
This paper cites URL https://proceedings.neurips.cc/paper/2020/file/ 99cad265a1768cc2dd013f0e740300ae-Paper.pdf.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction URL https://proceedings.neurips.cc/paper/2020/file/ 99cad265a1768cc2dd013f0e740300ae-Paper.pdf
Reference 47
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 2b626685-69b0-4dde-854f-819e6a477083 · outbound
This paper cites Molecular contrastive learning of representations via graph neural networks.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Molecular contrastive learning of representations via graph neural networks
Reference 48
- Resolution
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Observation 2448fa9a-989e-4772-b4c8-7492c344aebd · outbound
This paper cites Pedregosa, G.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Pedregosa, G
Reference 53
- Resolution
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Source-reported events for the cited work
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Observation 3b4af83f-b7e9-44b5-81fd-8d8983553359 · outbound
This paper cites A Appendix A.1 Models We used the following models to evaluate the effectiveness of the SQRL approach: Baselines.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction A Appendix A.1 Models We used the following models to evaluate the effectiveness of the SQRL approach: Baselines
Reference 2011
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation c4e8deef-c880-44d0-bad3-141a0ebd6ac7 · outbound
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Reference 2013
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Observation 06fd9ba7-d77e-4937-9e47-27e2edb310f4 · outbound
This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction RoBERTa: A Robustly Optimized BERT Pretraining Approach
Reference 2019
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Unavailable: canonical work link unavailable.
Observation 2f546c37-a5cd-46b8-bda3-d291ac3036dc · outbound
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Reference 2020
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- raw_fallback, observed 2026-08-10T20:14:55.214279Z
Source-reported events for the cited work
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Observation fd55eec1-3d35-42da-b4e9-a6a9f80f001b · outbound
This paper cites E(n) Equivariant Graph Neural Networks.
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction E(n) Equivariant Graph Neural Networks
Reference 2022
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- no resolver link, observed 2026-08-10T20:14:54.367458Z
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Pith citing papers
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