Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T20:12:24.128648Z
Paper Citation Record · LEDGER
Physics-informed deep learning for infectious disease forecasting
As of 16 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 1 inbound Pith citation observation for arXiv:2501.09298.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-28T15:42:58.769940Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
69 of 69 outbound references displayed
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External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
Observation e715d197-0a41-4fe1-898c-edf69e4f6c6e · outbound
This paper cites Provisional mortality data—united states, 2021.
Physics-informed deep learning for infectious disease forecasting Provisional mortality data—united states, 2021
Reference 1
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0e5f4082-e228-4216-a638-9d6cfd9a3a4f · outbound
This paper cites The challenge of emerging and re-emerging infectious diseases.
Physics-informed deep learning for infectious disease forecasting The challenge of emerging and re-emerging infectious diseases
Reference 2
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1740ba75-936d-4f53-80fb-d1396c07d65a · outbound
This paper cites Climate change increases cross-species viral transmission risk.
Physics-informed deep learning for infectious disease forecasting Climate change increases cross-species viral transmission risk
Reference 3
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 66c252bc-ac5c-4208-a556-4f60a8005c63 · outbound
This paper cites Improving pandemic response: employing mathematical modeling to confront coronavirus disease 2019.
Physics-informed deep learning for infectious disease forecasting Improving pandemic response: employing mathematical modeling to confront coronavirus disease 2019
Reference 4
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3c8db71d-f75f-40bb-84d2-361dee9e2c58 · outbound
This paper cites Applying infectious disease forecasting to public health: a path forward using influenza fore- casting examples.
Physics-informed deep learning for infectious disease forecasting Applying infectious disease forecasting to public health: a path forward using influenza fore- casting examples
Reference 5
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7970ad41-ce9d-453d-bd0c-00698bc999ec · outbound
This paper cites An accurate hierarchical model to forecast diverse seasonal infectious diseases.
Physics-informed deep learning for infectious disease forecasting An accurate hierarchical model to forecast diverse seasonal infectious diseases
Reference 6
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation be2423b9-73e4-4e78-8bde-fb9cb7acd000 · outbound
This paper cites Infectious Diseases of Humans.
Physics-informed deep learning for infectious disease forecasting Infectious Diseases of Humans
Reference 7
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f97bea27-7697-4ab8-85b7-a7fdd4ef94d4 · outbound
This paper cites Modelling Infectious Diseases: In Humans and Animals.
Physics-informed deep learning for infectious disease forecasting Modelling Infectious Diseases: In Humans and Animals
Reference 8
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a0d52093-51f9-4577-b9ab-42ad5fca9cdd · outbound
This paper cites Compartmental models in epidemiology.
Physics-informed deep learning for infectious disease forecasting Compartmental models in epidemiology
Reference 9
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d303a178-6f28-4654-a34a-633595f7a6ae · outbound
This paper cites Mathematical models in epidemiology, volume 32.
Physics-informed deep learning for infectious disease forecasting Mathematical models in epidemiology, volume 32
Reference 10
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 262b8a74-023a-4f8e-a521-7b33ad98b350 · outbound
This paper cites An introduction to mathematical epidemiology , volume 61.
Physics-informed deep learning for infectious disease forecasting An introduction to mathematical epidemiology , volume 61
Reference 11
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3f6a3f78-41ea-4d08-9d8e-6aa67474fec3 · outbound
This paper cites Mathematical modelling and prediction in infectious disease epidemiology.
Physics-informed deep learning for infectious disease forecasting Mathematical modelling and prediction in infectious disease epidemiology
Reference 12
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d41bde73-8fc8-400b-acf2-183bdfb164f1 · outbound
This paper cites Appropriate Models for the Manage- ment of Infectious Diseases.
Physics-informed deep learning for infectious disease forecasting Appropriate Models for the Manage- ment of Infectious Diseases
Reference 13
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation db5c4b2d-a7b0-4b34-abf4-01abf1a7146c · outbound
This paper cites Structural identifiability and observability of compartmental models of the covid-19 pandemic.
Physics-informed deep learning for infectious disease forecasting Structural identifiability and observability of compartmental models of the covid-19 pandemic
Reference 14
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation bb0c3570-0fdf-4597-9bb3-798310650d87 · outbound
This paper cites A fractional-order compartmental model for the spread of the covid-19 pandemic.
Physics-informed deep learning for infectious disease forecasting A fractional-order compartmental model for the spread of the covid-19 pandemic
Reference 15
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 12a70365-1ac6-4f17-b337-1c09751ae20c · outbound
This paper cites Mathematical modeling of covid-19 transmission dynamics with a case study of wuhan.
Physics-informed deep learning for infectious disease forecasting Mathematical modeling of covid-19 transmission dynamics with a case study of wuhan
Reference 16
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e3b05c99-387e-48dd-9331-0e55c2991b74 · outbound
This paper cites Compartmental models of the covid-19 pandemic for physicians and physician-scientists.
Physics-informed deep learning for infectious disease forecasting Compartmental models of the covid-19 pandemic for physicians and physician-scientists
Reference 17
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e56dbf3f-12c2-4e57-a47f-3288681e301e · outbound
This paper cites Sirsi compartmental model for covid-19 pandemic with immunity loss.
Physics-informed deep learning for infectious disease forecasting Sirsi compartmental model for covid-19 pandemic with immunity loss
Reference 18
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 100bc043-8471-4146-998c-3bc3ac73beb5 · outbound
This paper cites New compartment model for covid-19.
Physics-informed deep learning for infectious disease forecasting New compartment model for covid-19
Reference 19
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7029237e-0928-47ff-8837-6594d3e02e6d · outbound
This paper cites an unresolved cited work.
Physics-informed deep learning for infectious disease forecasting Unresolved cited work
Reference 20
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 257a7d73-04b8-4daa-92b7-c666b6ff98b6 · outbound
This paper cites Measuring the impact of Ebola control measures in Sierra Leone.
Physics-informed deep learning for infectious disease forecasting Measuring the impact of Ebola control measures in Sierra Leone
Reference 21
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation fe6f9f09-5cf1-4ac2-a1cb-efbf93a34ad7 · outbound
This paper cites A semi-parametric, state-space compartmental model with time-dependent parameters for forecasting covid-19 cases, hospitalizations and deaths.
Physics-informed deep learning for infectious disease forecasting A semi-parametric, state-space compartmental model with time-dependent parameters for forecasting covid-19 cases, hospitalizations and deaths
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:25.071032Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f3f4950c-676e-485c-920f-776b7b9daf26 · outbound
This paper cites A data-driven semi-parametric model of sars-cov-2 trans- mission in the united states.
Physics-informed deep learning for infectious disease forecasting A data-driven semi-parametric model of sars-cov-2 trans- mission in the united states
Reference 23
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d1c8d9cc-0194-4dc2-ad08-6acfd4985f7a · outbound
This paper cites Real-time mechanistic bayesian forecasts of covid-19 mortality.
Physics-informed deep learning for infectious disease forecasting Real-time mechanistic bayesian forecasts of covid-19 mortality
Reference 24
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 67c4c92c-4215-426b-8acf-b8f32324e337 · outbound
This paper cites Deep learning for epidemio- logical predictions.
Physics-informed deep learning for infectious disease forecasting Deep learning for epidemio- logical predictions
Reference 25
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a68a8481-895c-4537-bfd9-9dbb6755fbed · outbound
This paper cites Deep learning for few-shot white blood cell image classification and feature learning.
Physics-informed deep learning for infectious disease forecasting Deep learning for few-shot white blood cell image classification and feature learning
Reference 26
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 00ad2aed-40e2-44d3-a4d8-3a19e66a6954 · outbound
This paper cites A systematic study of the performance of machine learning models on analyzing the association between semen quality and environmental pollutants.
Physics-informed deep learning for infectious disease forecasting A systematic study of the performance of machine learning models on analyzing the association between semen quality and environmental pollutants
Reference 27
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 83464cae-cdf0-46e0-8e0a-f94f0f683b81 · outbound
This paper cites A deep learning model for efficient end-to-end stratification of thrombotic risk in left atrial appendage.
Physics-informed deep learning for infectious disease forecasting A deep learning model for efficient end-to-end stratification of thrombotic risk in left atrial appendage
Reference 28
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation af3f3328-3e87-4b06-a6d5-cf7ca2093877 · outbound
This paper cites Mathematical models for predicting covid-19 pandemic: a review.
Physics-informed deep learning for infectious disease forecasting Mathematical models for predicting covid-19 pandemic: a review
Reference 29
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 26a2815d-5d03-499e-a93d-d8587ee17e31 · outbound
This paper cites Kevrekidis, Lu Lu, Paris Perdikaris, Sifan Wang, and Liu Yang.
Physics-informed deep learning for infectious disease forecasting Kevrekidis, Lu Lu, Paris Perdikaris, Sifan Wang, and Liu Yang
Reference 30
- Resolution
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Source-reported events for the cited work
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Observation 863d2f4a-54ec-4ca4-9b69-226278b98a0f · outbound
This paper cites Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations.
Physics-informed deep learning for infectious disease forecasting Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations
Reference 31
- Resolution
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Source-reported events for the cited work
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Observation 2aac7962-8c6a-4819-be53-52205ce2bb0f · outbound
This paper cites Extraction of mechanical properties of materials through deep learning from instru- mented indentation.
Physics-informed deep learning for infectious disease forecasting Extraction of mechanical properties of materials through deep learning from instru- mented indentation
Reference 32
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation eeb70d79-738b-4c4b-9847-6f7b57110437 · outbound
This paper cites Multi-head physics-informed neural networks for learning functional priors and uncertainty quantification.
Physics-informed deep learning for infectious disease forecasting Multi-head physics-informed neural networks for learning functional priors and uncertainty quantification
Reference 33
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f8052219-6754-4400-bb7c-b9287f7cadc6 · outbound
This paper cites Correcting model misspecification in physics-informed neural networks (PINNs).
Physics-informed deep learning for infectious disease forecasting Correcting model misspecification in physics-informed neural networks (PINNs)
Reference 34
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f1c8d090-d0b2-40af-8354-130f8b63dda4 · outbound
This paper cites Discovering a reaction– diffusion model for Alzheimer’s disease by combining PINNs with symbolic regression.
Physics-informed deep learning for infectious disease forecasting Discovering a reaction– diffusion model for Alzheimer’s disease by combining PINNs with symbolic regression
Reference 35
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e2c1773f-4459-4c9c-b482-350b0b9e093f · outbound
This paper cites Uncertainty quantification for noisy inputs–outputs in physics-informed neural networks and neural operators.
Physics-informed deep learning for infectious disease forecasting Uncertainty quantification for noisy inputs–outputs in physics-informed neural networks and neural operators
Reference 36
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0542f176-ee9d-4849-a7f7-91f423397495 · outbound
This paper cites NeuralUQ: A com- prehensive library for uncertainty quantification in neural differential equations and operators.
Physics-informed deep learning for infectious disease forecasting NeuralUQ: A com- prehensive library for uncertainty quantification in neural differential equations and operators
Reference 37
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 08f273ec-1980-416e-999a-cf35d9d6a7da · outbound
This paper cites B-pinns: Bayesian physics-informed neu- ral networks for forward and inverse PDE problems with noisy data.
Physics-informed deep learning for infectious disease forecasting B-pinns: Bayesian physics-informed neu- ral networks for forward and inverse PDE problems with noisy data
Reference 38
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation cf8e6768-9d77-43b7-bf88-c33f3db0ee57 · outbound
This paper cites Ppinn: Parareal physics- informed neural network for time-dependent pdes.
Physics-informed deep learning for infectious disease forecasting Ppinn: Parareal physics- informed neural network for time-dependent pdes
Reference 39
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 8c374663-68e9-4c75-8e28-0b0b58664191 · outbound
This paper cites Gradient-enhanced physics- informed neural networks for forward and inverse pde problems.
Physics-informed deep learning for infectious disease forecasting Gradient-enhanced physics- informed neural networks for forward and inverse pde problems
Reference 40
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7f5a7ab4-ce1a-4eac-9c63-d1e442d7ce62 · outbound
This paper cites Physics-informed neural networks for solving forward and inverse flow problems via the boltzmann-bgk formulation.
Physics-informed deep learning for infectious disease forecasting Physics-informed neural networks for solving forward and inverse flow problems via the boltzmann-bgk formulation
Reference 41
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 95fd9431-a0ce-4e41-b34c-7da9670ddf22 · outbound
This paper cites Deepxde: A deep learning library for solving differential equations.
Physics-informed deep learning for infectious disease forecasting Deepxde: A deep learning library for solving differential equations
Reference 42
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b5339ccf-df8d-4cf4-996f-ed08cd7238a6 · outbound
This paper cites From PINNs to PIKANs: Recent advances in physics-informed machine learning.
Physics-informed deep learning for infectious disease forecasting From PINNs to PIKANs: Recent advances in physics-informed machine learning
Reference 43
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation cbe585dc-afd9-4b8b-8af1-1b4b0b59e256 · outbound
This paper cites Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations.
Physics-informed deep learning for infectious disease forecasting Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
Reference 44
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 24533a04-9032-426e-99b3-dcdded5ea88f · outbound
This paper cites Aoslo-net: a deep learning-based method for automatic segmentation of retinal microaneurysms from adaptive optics scanning laser ophthalmoscopy images.
Physics-informed deep learning for infectious disease forecasting Aoslo-net: a deep learning-based method for automatic segmentation of retinal microaneurysms from adaptive optics scanning laser ophthalmoscopy images
Reference 45
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation eda326dd-7e59-4f76-a23f-29bf2ec54e30 · outbound
This paper cites Tgm-nets: A deep learning framework for enhanced forecasting of tumor growth by integrating imaging and modeling.
Physics-informed deep learning for infectious disease forecasting Tgm-nets: A deep learning framework for enhanced forecasting of tumor growth by integrating imaging and modeling
Reference 46
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7f65faff-91c1-4536-83e1-34c849e7cf1b · outbound
This paper cites Transfer learning on physics-informed neural networks for tracking the hemodynamics in the evolving false lumen of dissected aorta.
Physics-informed deep learning for infectious disease forecasting Transfer learning on physics-informed neural networks for tracking the hemodynamics in the evolving false lumen of dissected aorta
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.586067Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation dff41b3c-f7ab-494c-837a-95932ff61d71 · outbound
This paper cites A deep neural network for operator learning enhanced by attention and gating mechanisms for long-time forecasting of tumor growth.
Physics-informed deep learning for infectious disease forecasting A deep neural network for operator learning enhanced by attention and gating mechanisms for long-time forecasting of tumor growth
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.567861Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7ffb3e30-48ff-4bdd-9492-f81afd8d9f6a · outbound
This paper cites Coagulo-net: Enhancing the mathematical modeling of blood coagulation using physics-informed neural networks.
Physics-informed deep learning for infectious disease forecasting Coagulo-net: Enhancing the mathematical modeling of blood coagulation using physics-informed neural networks
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.549492Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b7d2be43-a84f-40db-b8c8-65843667bcb9 · outbound
This paper cites Artificial intelligence velocimetry and microaneurysm-on-a-chip for three-dimensional analysis of blood flow in physiology and disease.
Physics-informed deep learning for infectious disease forecasting Artificial intelligence velocimetry and microaneurysm-on-a-chip for three-dimensional analysis of blood flow in physiology and disease
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.531454Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c57cfe4c-d352-4b1c-a7c5-4ff9b2ebf1c6 · outbound
This paper cites Bayesian physics informed neural networks for real-world nonlinear dynamical systems.
Physics-informed deep learning for infectious disease forecasting Bayesian physics informed neural networks for real-world nonlinear dynamical systems
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.512949Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ae81090d-3458-4f6b-b0fa-82f2d2010fa8 · outbound
This paper cites Thermodynamically consistent physics-informed neural networks for hyperbolic systems.
Physics-informed deep learning for infectious disease forecasting Thermodynamically consistent physics-informed neural networks for hyperbolic systems
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:12:24.028259Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0a36c28a-1025-44b3-bdf6-4ca3bbd502de · outbound
This paper cites A physics-informed op- erator regression framework for extracting data-driven continuum models.
Physics-informed deep learning for infectious disease forecasting A physics-informed op- erator regression framework for extracting data-driven continuum models
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.484075Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 55473a14-c3f2-4707-a535-83f4293bfaab · outbound
This paper cites Learning and discovering multiple solutions using physics-informed neural networks with random initialization and deep ensemble.
Physics-informed deep learning for infectious disease forecasting Learning and discovering multiple solutions using physics-informed neural networks with random initialization and deep ensemble
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:12:24.039618Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 26fff2ed-140e-4202-badc-3148f9b55e84 · outbound
This paper cites Evaluating epidemic forecasts in an interval format.
Physics-informed deep learning for infectious disease forecasting Evaluating epidemic forecasts in an interval format
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.466312Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3da30f93-1720-4601-99c4-a0b89d1c3a68 · outbound
This paper cites Ensemble forecasts of coronavirus disease 2019 (covid-19) in the us.
Physics-informed deep learning for infectious disease forecasting Ensemble forecasts of coronavirus disease 2019 (covid-19) in the us
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.444927Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3b25eaa8-8bb6-4a21-ab66-63b80e8e0521 · outbound
This paper cites An interactive web-based dashboard to track covid-19 in real time.
Physics-informed deep learning for infectious disease forecasting An interactive web-based dashboard to track covid-19 in real time
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.426327Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 72513860-7146-4de5-bb33-eb9cbbf3d915 · outbound
This paper cites An open reposi- tory of real-time covid-19 indicators.
Physics-informed deep learning for infectious disease forecasting An open reposi- tory of real-time covid-19 indicators
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.409223Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 87a05e2b-15dc-4dcc-b4a0-3288bbba1863 · outbound
This paper cites Google covid-19 community mobility reports.
Physics-informed deep learning for infectious disease forecasting Google covid-19 community mobility reports
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.392843Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9825b861-f701-4dd8-96c2-2466299a24c8 · outbound
This paper cites Adam: A Method for Stochastic Optimization.
Physics-informed deep learning for infectious disease forecasting Adam: A Method for Stochastic Optimization
Reference 60
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:12:24.075249Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 84aec14a-8ab5-49bc-aa19-7113e86c76b5 · outbound
This paper cites Another look at measures of forecast accuracy.
Physics-informed deep learning for infectious disease forecasting Another look at measures of forecast accuracy
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.375554Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4d201c23-6ea3-4ff0-a3fc-e12e95be50cc · outbound
This paper cites Recurrent neural networks.
Physics-informed deep learning for infectious disease forecasting Recurrent neural networks
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.357766Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9b7dccf8-ae6a-499a-9c5f-378820b764fd · outbound
This paper cites Long short-term memory.
Physics-informed deep learning for infectious disease forecasting Long short-term memory
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.340827Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 56795450-7252-46b8-8489-ff0b9db31ff7 · outbound
This paper cites Gate-variants of gated recurrent unit (gru) neural networks.
Physics-informed deep learning for infectious disease forecasting Gate-variants of gated recurrent unit (gru) neural networks
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.322010Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation acdbb1c4-14e1-4284-85fa-b6a8b69a06d1 · outbound
This paper cites Attention mechanism, transformers, bert, and gpt: tuto- rial and survey.
Physics-informed deep learning for infectious disease forecasting Attention mechanism, transformers, bert, and gpt: tuto- rial and survey
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.301964Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e21b55ad-b6eb-4189-9c9c-1e26f0633cd7 · outbound
This paper cites A physics-informed neural network to model covid- 19 infection and hospitalization scenarios.
Physics-informed deep learning for infectious disease forecasting A physics-informed neural network to model covid- 19 infection and hospitalization scenarios
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.283491Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation dcc4abfd-f286-48ba-a291-2b1dcf880109 · outbound
This paper cites Einns: epidemiologically-informed neural networks.
Physics-informed deep learning for infectious disease forecasting Einns: epidemiologically-informed neural networks
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.264268Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6bf6d75e-0b45-4139-9e80-8d456135e4f6 · outbound
This paper cites Physics-informed machine learning for the covid-19 pandemic: Adherence to social distancing and short-term predictions for eight coun- tries.
Physics-informed deep learning for infectious disease forecasting Physics-informed machine learning for the covid-19 pandemic: Adherence to social distancing and short-term predictions for eight coun- tries
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.245249Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 5c506693-a4c4-4e35-8123-40b7fc3d46d0 · outbound
This paper cites Neural networks for endemic measles dynamics: compar- ative analysis and integration with mechanistic models.
Physics-informed deep learning for infectious disease forecasting Neural networks for endemic measles dynamics: compar- ative analysis and integration with mechanistic models
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T20:12:24.226699Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
Observation a149a51e-d0e5-4c37-a507-f48320ceb681 · inbound
Using Machine Learning to Enhance Hyperparameter Optimization in Pandemic Modeling: Case study of COVID-19 Dynamics in Ghana cites this paper.
Using Machine Learning to Enhance Hyperparameter Optimization in Pandemic Modeling: Case study of COVID-19 Dynamics in Ghana Physics-informed deep learning for infectious disease forecasting
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T15:52:21.846817Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.