Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda | Paper Citation Record

Observation d5dce593-7649-4bc7-af85-96d6d9268d94 · outbound

This paper cites Deep learning,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Deep learning,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T15:39:17.721774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cb80e24-dd0b-4316-ae63-be731276f5b4 · outbound

This paper cites A survey on deep learning and its applications,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda A survey on deep learning and its applications,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.872549Z

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 555a19aa-2e3e-4fea-ba3d-953ef6b24498 · outbound

This paper cites Deep learning is hitting a wall,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Deep learning is hitting a wall,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.857455Z

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 ad6cd2e2-01a6-41f5-ba74-a8afcc33992b · outbound

This paper cites an unresolved cited work.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:39:18.841823Z

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 dd217b33-2202-44e1-840a-10ad40888ddc · outbound

This paper cites Causality: The next step in artificial intelligence,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Causality: The next step in artificial intelligence,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.826917Z

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 8f0aa25d-8b57-43b6-b0b5-38d563bcc31d · outbound

This paper cites Causal Deep Learning.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Causal Deep Learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T15:39:17.745500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfac05aa-dd75-492c-8ebc-178110ca41af · outbound

This paper cites When causal inference meets deep learning,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda When causal inference meets deep learning,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.812072Z

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 4bf8c6da-eaba-446f-8c0f-bef13f485ceb · outbound

This paper cites Do humans think causally, and how?.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Do humans think causally, and how?

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.796447Z

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 ddd627b2-50d5-4fbd-b3c1-0761ef73d1ac · outbound

This paper cites When noise meets chaos: Stochastic resonance in neurochaos learning,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda When noise meets chaos: Stochastic resonance in neurochaos learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.780434Z

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 8fb40fd3-bebc-4221-b752-6cc85c3ab759 · outbound

This paper cites Neurochaos feature transformation for machine learning,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Neurochaos feature transformation for machine learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.764463Z

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 4dbf084b-77d3-448d-9de3-91ef698039b9 · outbound

This paper cites Causality preserving chaotic transformation and classification using neurochaos learning,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Causality preserving chaotic transformation and classification using neurochaos learning,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.749061Z

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 c7f00047-756a-4276-8467-71275c3e575f · outbound

This paper cites Linked data: Principles and state of the art,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Linked data: Principles and state of the art,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.733432Z

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 84c944eb-2aa6-4474-92b9-12e5b7cd6615 · outbound

This paper cites Opportunities for neuromorphic computing algorithms and applications,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Opportunities for neuromorphic computing algorithms and applications,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.717253Z

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 4b90f43b-85ed-48f9-b874-5677ca824d18 · outbound

This paper cites Pearl and D.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Pearl and D

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T15:39:17.782962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5c21281-11d4-4c3b-a005-b4524aefd82d · outbound

This paper cites Pearl, M.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Pearl, M

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T15:39:17.788263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12b11960-3a64-4d5f-b868-6531ac12a0eb · outbound

This paper cites An introduction to causal inference,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda An introduction to causal inference,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T15:39:17.792653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87a36696-ee78-419f-b307-436ce9c35823 · outbound

This paper cites A tutorial on learning with bayesian networks,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda A tutorial on learning with bayesian networks,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.674537Z

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 8e6d1223-9356-477c-839e-3d6fc9f0254b · outbound

This paper cites Causalkg: Causal knowledge graph explain- ability using interventional and counterfactual reasoning,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Causalkg: Causal knowledge graph explain- ability using interventional and counterfactual reasoning,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.658053Z

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 9225f7b5-79d9-4787-9cea-dca39bb1d5ca · outbound

This paper cites Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.641042Z

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 b94bec2d-7c34-4d42-bf4c-242133b18b41 · outbound

This paper cites Stochastic resonance in climatic change,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Stochastic resonance in climatic change,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.625029Z

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 5ad7a0e5-6053-40ed-87f3-cbcd061af7e6 · outbound

This paper cites Neurochaos inspired hybrid machine learning architecture for classification,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Neurochaos inspired hybrid machine learning architecture for classification,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.609511Z

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 36ffa979-91cc-4e46-888e-0bc1a78aa7ec · outbound

This paper cites Chaosnet: A chaos based artificial neural network architecture for classification,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Chaosnet: A chaos based artificial neural network architecture for classification,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.593978Z

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 269714db-f8c3-47c9-929b-5ab3428c95af · outbound

This paper cites What is a support vector machine?.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda What is a support vector machine?

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.578994Z

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 34d23e71-b8ef-40ed-87ee-2ff77f83eb1a · outbound

This paper cites Relating Graph Neural Networks to Structural Causal Models.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Relating Graph Neural Networks to Structural Causal Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T15:39:17.829950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 278f4085-7807-41ff-81e5-3f8ec740791c · outbound

This paper cites Link prediction based on graph neural net- works,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Link prediction based on graph neural net- works,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T15:39:17.836089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6afe4c7-0194-4022-b88b-7d2f9fb9703a · outbound

This paper cites Graph neu- ral networks and reinforcement learning: A survey,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Graph neu- ral networks and reinforcement learning: A survey,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.553984Z

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 887b0bf8-e8d8-439f-a593-df903aca534b · outbound

This paper cites an unresolved cited work.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:39:18.538881Z

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 a3d3bdf1-7deb-48d4-a223-7332c3071952 · outbound

This paper cites The semantic web,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda The semantic web,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.522848Z

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 236062ba-3fd6-4b5a-b4dc-e36c5c8bd5e9 · outbound

This paper cites Exploring Causal Learning through Graph Neural Networks: An In-depth Review.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Exploring Causal Learning through Graph Neural Networks: An In-depth Review

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T15:39:17.857687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5bf38f0-3829-4eab-84e8-5b148cf0457f · outbound

This paper cites Estimation of the kullback-leibler divergence,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Estimation of the kullback-leibler divergence,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.507460Z

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 43bb2c2c-009d-439a-980a-47ce3e2f26ef · outbound

This paper cites an unresolved cited work.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:39:18.492535Z

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 c8e31dbe-3208-4df0-82de-a2b8c3ba6d5e · outbound

This paper cites an unresolved cited work.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:39:18.476264Z

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 540f895a-38a5-40e7-a132-2f60a556d0f5 · outbound

This paper cites an unresolved cited work.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:39:18.459203Z

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 5d631631-1068-4dc8-8f92-5ecfbfb351b4 · outbound

This paper cites Causal graphsage: A robust graph method for classification based on causal sampling,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Causal graphsage: A robust graph method for classification based on causal sampling,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.443528Z

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 57102a48-7464-4a45-8fcc-6188fc18c671 · outbound

This paper cites Inductive representation learning on large graphs,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Inductive representation learning on large graphs,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T15:39:17.888098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17aee5a7-0182-4a88-802f-0c73336b40ec · outbound

This paper cites Logistic map: A possible random-number generator,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Logistic map: A possible random-number generator,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.418753Z

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 8188853e-454e-426a-86c0-254d97461ae1 · outbound

This paper cites Robust neural networks using stochastic resonance neurons,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Robust neural networks using stochastic resonance neurons,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.404445Z

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 499f452d-817f-47b9-b264-c9c55c523023 · outbound

This paper cites Neural spiking for causal inference and learning,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Neural spiking for causal inference and learning,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.389247Z

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 64a24310-fcd4-4e85-80f0-1b955e75d4ee · outbound

This paper cites Signn: A spike- induced graph neural network for dynamic graph representation learn- ing,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Signn: A spike- induced graph neural network for dynamic graph representation learn- ing,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.373978Z

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 03f38cd9-4118-4f09-89e0-19d95e16796d · outbound

This paper cites an unresolved cited work.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Unresolved cited work

Reference 40

Resolution: unresolved; raw_fallback, observed 2026-08-10T15:39:18.359077Z

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 808b335f-ec7a-4811-957c-fa704875824e · outbound

This paper cites Stochastic graph as a model for social networks,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Stochastic graph as a model for social networks,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.343628Z

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 7573e7c3-476a-4bcc-ab4a-faffe554bdc4 · outbound

This paper cites Graph Neural Stochastic Differential Equations.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Graph Neural Stochastic Differential Equations

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-08-10T15:39:18.132157Z

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 b11d67ca-f945-43f0-a3e2-e44c3581a4f0 · outbound

This paper cites A brain-inspired causal reasoning model based on spiking neural networks,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda A brain-inspired causal reasoning model based on spiking neural networks,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.328760Z

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 b0c5255c-9c84-46c2-8a0b-9286e1ce48a0 · outbound

This paper cites Random features strengthen graph neural networks,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Random features strengthen graph neural networks,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.314497Z

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 893d77a5-d040-4ad5-8caa-6fb457b2c138 · outbound

This paper cites Stochastic Aggregation in Graph Neural Networks.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Stochastic Aggregation in Graph Neural Networks

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-10T15:39:18.110773Z

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 deffdef0-f509-4707-8380-a39047c49369 · outbound

This paper cites Mapping the Neuro-Symbolic AI Landscape by Architectures: A Handbook on Augmenting Deep Learning Through Symbolic Reasoning.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Mapping the Neuro-Symbolic AI Landscape by Architectures: A Handbook on Augmenting Deep Learning Through Symbolic Reasoning

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-10T15:39:17.938080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d662f1ad-c86d-4472-8b86-baa77b4c416d · outbound

This paper cites Emergence of scaling in random net- works,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Emergence of scaling in random net- works,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.298556Z

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 d97bcfb5-d7f3-498e-bc6e-3bd7f5d0f522 · outbound

This paper cites Predicting missing links via local information,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Predicting missing links via local information,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.282666Z

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 9690b977-6d3d-4dd3-a70d-4284ff0e4f17 · outbound

This paper cites Customized Subgraph Selection and Encoding for Drug-drug Interaction Prediction.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Customized Subgraph Selection and Encoding for Drug-drug Interaction Prediction

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-08-10T15:39:18.072055Z

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 591b9534-aad3-40f4-9f4c-b0cea9a0b83c · outbound

This paper cites Efficient reinforcement learning through evolving neural network topologies,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Efficient reinforcement learning through evolving neural network topologies,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.266640Z

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 df79a58e-78d6-44c3-b852-879aaf232efc · outbound

This paper cites De novo drug design using reinforcement learning with graph-based deep generative models,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda De novo drug design using reinforcement learning with graph-based deep generative models,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.250719Z

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 5e76c4c5-8edd-4840-9f72-eba580f2375a · outbound

This paper cites Graph networks for molecular design,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Graph networks for molecular design,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.236336Z

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 313e2b09-bdeb-466d-ba51-fa5245d162d4 · outbound

This paper cites A purely spiking approach to reinforcement learning,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda A purely spiking approach to reinforcement learning,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.221316Z

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 0da3a7fb-b90f-4844-b856-000c8313950d · outbound

This paper cites CausalLP: Learning causal relations with weighted knowledge graph link prediction.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda CausalLP: Learning causal relations with weighted knowledge graph link prediction

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-10T15:39:17.977798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9a5d2cf-7c55-4e04-8b39-b1b7474fae79 · outbound

This paper cites Relation semantic fusion in subgraph for inductive link prediction in knowledge graphs,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Relation semantic fusion in subgraph for inductive link prediction in knowledge graphs,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.207237Z

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 9c19f7d4-5ec3-4a83-b46f-aa2a5ec10277 · outbound

This paper cites Higher-order link prediction via light hypergraph neural network and hybrid aggregator,.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Higher-order link prediction via light hypergraph neural network and hybrid aggregator,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:39:18.192413Z

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 7edbfd29-1738-4f3c-b332-857b31dc8198 · outbound

This paper cites Temporal Knowledge Graph Completion: A Survey.

Integrating Causality with Neurochaos Learning: Proposed Approach and Research Agenda Temporal Knowledge Graph Completion: A Survey

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-10T15:39:17.992342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers