Paper Citation Record · LEDGER

A Deep State Space Model for Rainfall-Runoff Simulations

As of 19 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 1 inbound Pith citation observation for arXiv:2501.14980.

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

pith.paper-citation-record.v1
2501.14980 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:47:45.717499Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:49:30.561262Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T21:49:30.685346Z

Reference resolution

56 of 56 outbound references displayed

verified exact2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 88a40a3b-7646-403d-ab1e-349a7542298e · outbound

This paper cites write newline.

A Deep State Space Model for Rainfall-Runoff Simulations write newline

Reference 1

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Source-reported events for the cited work

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Observation 1f555648-f8f3-43ad-8880-478f0b3697f7 · outbound

This paper cites The camels data set: catchment attributes and meteorology for large-sample studies.

A Deep State Space Model for Rainfall-Runoff Simulations The camels data set: catchment attributes and meteorology for large-sample studies

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.561675Z

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Observation 0f9a2aed-9e99-4626-819d-90980676fd06 · outbound

This paper cites Spectral State Space Models.

A Deep State Space Model for Rainfall-Runoff Simulations Spectral State Space Models

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-10T14:47:45.875677Z

Source-reported events for the cited work

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Observation 6a494550-ca80-4386-a98c-a7e2c34be1b1 · outbound

This paper cites Sacramento soil moisture accounting model (sac-sma).

A Deep State Space Model for Rainfall-Runoff Simulations Sacramento soil moisture accounting model (sac-sma)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.546389Z

Source-reported events for the cited work

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Observation 634d8350-5ce5-4f06-bc57-10539a6926bd · outbound

This paper cites Basri, D.

A Deep State Space Model for Rainfall-Runoff Simulations Basri, D

Reference 5

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Observation e01311e3-ff6e-4f96-a667-67b787d96297 · outbound

This paper cites Changing ideas in hydrology—the case of physically-based models.

A Deep State Space Model for Rainfall-Runoff Simulations Changing ideas in hydrology—the case of physically-based models

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.518220Z

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Observation b2b35bb5-8c1a-4464-9b41-149f1c9de7e1 · outbound

This paper cites A discussion of distributed hydrological modelling.

A Deep State Space Model for Rainfall-Runoff Simulations A discussion of distributed hydrological modelling

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.501716Z

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Observation 8062be85-d93a-4b77-84b2-d50190063568 · outbound

This paper cites Rainfall-runoff modelling: the primer.

A Deep State Space Model for Rainfall-Runoff Simulations Rainfall-runoff modelling: the primer

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.486978Z

Source-reported events for the cited work

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Observation 6a5618a3-8064-47a9-bf73-a4115badc8e5 · outbound

This paper cites A physically based, variable contributing area model of basin hydrology/un mod \`e le \`a base physique de zone d'appel variable de l'hydrologie du bassin versant.

A Deep State Space Model for Rainfall-Runoff Simulations A physically based, variable contributing area model of basin hydrology/un mod \`e le \`a base physique de zone d'appel variable de l'hydrologie du bassin versant

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.472583Z

Source-reported events for the cited work

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Observation 9074d273-97fd-47fd-98cd-f95509f076ce · outbound

This paper cites Future streamflow regime changes in the united states: assessment using functional classification.

A Deep State Space Model for Rainfall-Runoff Simulations Future streamflow regime changes in the united states: assessment using functional classification

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.457954Z

Source-reported events for the cited work

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Observation 76d3b5e8-c1c3-4461-b92d-4df91c76e44f · outbound

This paper cites The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism.

A Deep State Space Model for Rainfall-Runoff Simulations The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.443323Z

Source-reported events for the cited work

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Observation 87d2c95d-613d-4830-8adf-90b045e0fba4 · outbound

This paper cites Lipschitz recurrent neural networks.

A Deep State Space Model for Rainfall-Runoff Simulations Lipschitz recurrent neural networks

Reference 12

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Observation 17f4c084-7f97-41a5-b407-f83d1be3ca27 · outbound

This paper cites Gated Recurrent Neural Networks with Weighted Time-Delay Feedback.

A Deep State Space Model for Rainfall-Runoff Simulations Gated Recurrent Neural Networks with Weighted Time-Delay Feedback

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-10T14:47:45.854677Z

Source-reported events for the cited work

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Observation b8a2d6f2-3667-480a-9ee2-eede5debd4fc · outbound

This paper cites Differentiable, learnable, regionalized process-based models with multiphysical outputs can approach state-of-the-art hydrologic prediction accuracy.

A Deep State Space Model for Rainfall-Runoff Simulations Differentiable, learnable, regionalized process-based models with multiphysical outputs can approach state-of-the-art hydrologic prediction accuracy

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.419762Z

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Observation 65ae1bdd-7daf-48dc-9486-08baa17e962b · outbound

This paper cites Deep learning rainfall--runoff predictions of extreme events.

A Deep State Space Model for Rainfall-Runoff Simulations Deep learning rainfall--runoff predictions of extreme events

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.404695Z

Source-reported events for the cited work

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Observation be301323-4998-4b21-ab6b-b488e8a9b46f · outbound

This paper cites On strictly enforced mass conservation constraints for modelling the rainfall-runoff process.

A Deep State Space Model for Rainfall-Runoff Simulations On strictly enforced mass conservation constraints for modelling the rainfall-runoff process

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.388302Z

Source-reported events for the cited work

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Observation b9150cc1-3b51-4409-a45c-40efe0b2ee17 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

A Deep State Space Model for Rainfall-Runoff Simulations Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 17

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Source-reported events for the cited work

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Observation 22f9a760-b6e6-410b-884c-2cc0d6a2fe43 · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

A Deep State Space Model for Rainfall-Runoff Simulations Efficiently Modeling Long Sequences with Structured State Spaces

Reference 18

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Source-reported events for the cited work

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Observation ebe33560-3db2-422f-b3f3-1d45320b127d · outbound

This paper cites Combining recurrent, convolutional, and continuous-time models with linear state space layers.

A Deep State Space Model for Rainfall-Runoff Simulations Combining recurrent, convolutional, and continuous-time models with linear state space layers

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.373998Z

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Observation 1f37ffbd-388e-41c1-8594-5b471465a47e · outbound

This paper cites On the parameterization and initialization of diagonal state space models.

A Deep State Space Model for Rainfall-Runoff Simulations On the parameterization and initialization of diagonal state space models

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.359231Z

Source-reported events for the cited work

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Observation d5ec9f09-8ad0-4cdd-9f01-0c455cbaf359 · outbound

This paper cites Decomposition of the mean squared error and nse performance criteria: Implications for improving hydrological modelling.

A Deep State Space Model for Rainfall-Runoff Simulations Decomposition of the mean squared error and nse performance criteria: Implications for improving hydrological modelling

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.345058Z

Source-reported events for the cited work

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Observation 670a88d2-dbbf-4f1e-9756-ac80cbeea9d4 · outbound

This paper cites Liquid structural state-space models.

A Deep State Space Model for Rainfall-Runoff Simulations Liquid structural state-space models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.330178Z

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Observation e47ac7a0-f023-4830-9dc4-4f181738e359 · outbound

This paper cites Long short-term memory.

A Deep State Space Model for Rainfall-Runoff Simulations Long short-term memory

Reference 23

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Source-reported events for the cited work

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Observation 27849d3f-0818-4846-bc26-25c19b723315 · outbound

This paper cites Mc-lstm: Mass-conserving lstm.

A Deep State Space Model for Rainfall-Runoff Simulations Mc-lstm: Mass-conserving lstm

Reference 24

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Source-reported events for the cited work

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Observation e7e91a82-408b-4d9d-959e-09cd0d4d73e8 · outbound

This paper cites Physics-informed neural network for diffusive wave model.

A Deep State Space Model for Rainfall-Runoff Simulations Physics-informed neural network for diffusive wave model

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.291857Z

Source-reported events for the cited work

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Observation 7df80393-c282-4e1d-8a77-84d1dbd0f24b · outbound

This paper cites Groundwater inverse modeling: Physics-informed neural network with disentangled constraints and errors.

A Deep State Space Model for Rainfall-Runoff Simulations Groundwater inverse modeling: Physics-informed neural network with disentangled constraints and errors

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.277847Z

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Observation c66f7b5e-009b-4f99-94a9-30f2c83a676c · outbound

This paper cites A review of rainfall-runoff modeling for stormwater management.

A Deep State Space Model for Rainfall-Runoff Simulations A review of rainfall-runoff modeling for stormwater management

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.263439Z

Source-reported events for the cited work

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Observation 9099d3e7-7bba-4507-8ad7-315ace5d6e28 · outbound

This paper cites Toward improved predictions in ungauged basins: Exploiting the power of machine learning.

A Deep State Space Model for Rainfall-Runoff Simulations Toward improved predictions in ungauged basins: Exploiting the power of machine learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.248842Z

Source-reported events for the cited work

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Observation 8e42baef-7be4-45be-acc3-c176a6e83e6b · outbound

This paper cites Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets.

A Deep State Space Model for Rainfall-Runoff Simulations Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.234596Z

Source-reported events for the cited work

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Observation 3f03272d-4d24-485a-b066-22abff095be2 · outbound

This paper cites Hydrological concept formation inside long short-term memory (lstm) networks.

A Deep State Space Model for Rainfall-Runoff Simulations Hydrological concept formation inside long short-term memory (lstm) networks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.219593Z

Source-reported events for the cited work

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Observation 82cf2f0a-6c84-49b2-846b-0a0386f7346e · outbound

This paper cites Elucidating the Design Choice of Probability Paths in Flow Matching for Forecasting.

A Deep State Space Model for Rainfall-Runoff Simulations Elucidating the Design Choice of Probability Paths in Flow Matching for Forecasting

Reference 31

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Source-reported events for the cited work

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Observation 2188850a-213b-4fea-9ab9-1e1b13ce11fd · outbound

This paper cites Probing the limit of hydrologic predictability with the transformer network.

A Deep State Space Model for Rainfall-Runoff Simulations Probing the limit of hydrologic predictability with the transformer network

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.205177Z

Source-reported events for the cited work

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Observation 05c2e8bc-d2e3-46e6-aae1-9ead4701f925 · outbound

This paper cites General review of rainfall-runoff modeling: model calibration, data assimilation, and uncertainty analysis.

A Deep State Space Model for Rainfall-Runoff Simulations General review of rainfall-runoff modeling: model calibration, data assimilation, and uncertainty analysis

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.191030Z

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Observation 68b6a8cb-8f70-4eee-a27b-b26908d17ad0 · outbound

This paper cites Generative modeling of regular and irregular time series data via koopman vaes.

A Deep State Space Model for Rainfall-Runoff Simulations Generative modeling of regular and irregular time series data via koopman vaes

Reference 34

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Observation d3948f0c-f4cb-4c9b-850b-d9a2ea52b895 · outbound

This paper cites River flow forecasting through conceptual models part i—a discussion of principles.

A Deep State Space Model for Rainfall-Runoff Simulations River flow forecasting through conceptual models part i—a discussion of principles

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.161946Z

Source-reported events for the cited work

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Observation 44ca9973-e99c-499d-a0a7-3370f72c9d90 · outbound

This paper cites an unresolved cited work.

A Deep State Space Model for Rainfall-Runoff Simulations Unresolved cited work

Reference 36

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Source-reported events for the cited work

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Observation 4b97ce25-98cf-44f4-972c-a08f4848f878 · outbound

This paper cites State-Free Inference of State-Space Models: The Transfer Function Approach.

A Deep State Space Model for Rainfall-Runoff Simulations State-Free Inference of State-Space Models: The Transfer Function Approach

Reference 37

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Observation bddd1528-cf7e-4206-bc42-7e5c3df6ddbd · outbound

This paper cites Mamba-360: Survey of State Space Models as Transformer Alternative for Long Sequence Modelling: Methods, Applications, and Challenges.

A Deep State Space Model for Rainfall-Runoff Simulations Mamba-360: Survey of State Space Models as Transformer Alternative for Long Sequence Modelling: Methods, Applications, and Challenges

Reference 38

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Source-reported events for the cited work

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Observation f61301df-8e90-4910-95b5-31959aea032f · outbound

This paper cites Evaluation of random forests for short-term daily streamflow forecasting in rainfall-and snowmelt-driven watersheds.

A Deep State Space Model for Rainfall-Runoff Simulations Evaluation of random forests for short-term daily streamflow forecasting in rainfall-and snowmelt-driven watersheds

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.132594Z

Source-reported events for the cited work

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Observation 92fb53aa-e476-438f-9f85-6b21aec4c31b · outbound

This paper cites Long expressive memory for sequence modeling.

A Deep State Space Model for Rainfall-Runoff Simulations Long expressive memory for sequence modeling

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.118174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 43cd202b-efe0-4e02-8aa5-a268031af88a · outbound

This paper cites Differentiable modelling to unify machine learning and physical models for geosciences.

A Deep State Space Model for Rainfall-Runoff Simulations Differentiable modelling to unify machine learning and physical models for geosciences

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.103722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8ac28e39-ad48-4b00-bee8-72964a457ed6 · outbound

This paper cites Smith, Andrew Warrington, and Scott Linderman.

A Deep State Space Model for Rainfall-Runoff Simulations Smith, Andrew Warrington, and Scott Linderman

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.088395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 98ccc989-17ae-4851-a0a9-1c793e9fcb9f · outbound

This paper cites From calibration to parameter learning: Harnessing the scaling effects of big data in geoscientific modeling.

A Deep State Space Model for Rainfall-Runoff Simulations From calibration to parameter learning: Harnessing the scaling effects of big data in geoscientific modeling

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.071796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5cbbc090-018a-4253-bc11-5b75ae2a8af6 · outbound

This paper cites Attention is all you need.

A Deep State Space Model for Rainfall-Runoff Simulations Attention is all you need

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.055283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c1c8209a-fa74-4187-b40d-adde0c2b0af9 · outbound

This paper cites StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization.

A Deep State Space Model for Rainfall-Runoff Simulations StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-10T14:47:45.659626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c35e0a9c-2084-45ea-a751-8bb43fca5df5 · outbound

This paper cites Continental-scale water and energy flux analysis and validation for the north american land data assimilation system project phase 2 (nldas-2): 1.

A Deep State Space Model for Rainfall-Runoff Simulations Continental-scale water and energy flux analysis and validation for the north american land data assimilation system project phase 2 (nldas-2): 1

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.040623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eb6ccc97-92ed-42c2-a2d3-b8e083c4d104 · outbound

This paper cites Classification of watersheds in the conterminous united states using shape-based time-series clustering and random forests.

A Deep State Space Model for Rainfall-Runoff Simulations Classification of watersheds in the conterminous united states using shape-based time-series clustering and random forests

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:46.022704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e5e96fe8-5f1d-4661-8131-d55e0e39f72d · outbound

This paper cites A process-based diagnostic approach to model evaluation: Application to the nws distributed hydrologic model.

A Deep State Space Model for Rainfall-Runoff Simulations A process-based diagnostic approach to model evaluation: Application to the nws distributed hydrologic model

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:45.995561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b6616096-66d6-4990-9334-c9fe8f2f6023 · outbound

This paper cites Tuning frequency bias in neural network training with nonuniform data.

A Deep State Space Model for Rainfall-Runoff Simulations Tuning frequency bias in neural network training with nonuniform data

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:45.979389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9950966d-5dea-4166-ae8f-42e7e8d4f9c7 · outbound

This paper cites Mahoney, and N.

A Deep State Space Model for Rainfall-Runoff Simulations Mahoney, and N

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:45.964839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8996d645-e3e7-4a3f-a2f8-4ae86fb7d853 · outbound

This paper cites Tuning frequency bias of state space models.

A Deep State Space Model for Rainfall-Runoff Simulations Tuning frequency bias of state space models

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:45.949392Z

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Observation 5183c260-50ef-41ee-b4b7-8e37870993f8 · outbound

This paper cites Hope for a robust parameterization of long-memory state space models.

A Deep State Space Model for Rainfall-Runoff Simulations Hope for a robust parameterization of long-memory state space models

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:45.934726Z

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Observation 103f07a9-46bd-4e4c-9ff8-ab06013c8284 · outbound

This paper cites Deep latent state space models for time-series generation.

A Deep State Space Model for Rainfall-Runoff Simulations Deep latent state space models for time-series generation

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:47:45.919099Z

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Observation ccbbec75-2bc5-4f54-aaca-68d0da828252 · outbound

This paper cites @esa (Ref.

A Deep State Space Model for Rainfall-Runoff Simulations @esa (Ref

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-10T14:47:45.706942Z

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Observation b36a1a9d-d0ab-4a20-9b63-2d8b54b0f446 · outbound

This paper cites an unresolved cited work.

A Deep State Space Model for Rainfall-Runoff Simulations Unresolved cited work

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-10T14:47:45.711871Z

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Observation 31ab8536-b43f-41bd-a441-1ba573169ed4 · outbound

This paper cites an unresolved cited work.

A Deep State Space Model for Rainfall-Runoff Simulations Unresolved cited work

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-10T14:47:45.717499Z

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Pith citing papers

Observation a95c8129-a7e9-49be-aa05-6ca47f2c7040 · inbound

Block-Biased Mamba for Long-Range Sequence Processing cites this paper.

Block-Biased Mamba for Long-Range Sequence Processing A Deep State Space Model for Rainfall-Runoff Simulations

Reference 90

Resolution: verified exact; local_arxiv, observed 2026-08-15T21:49:30.691078Z

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