Pith. sign in

Paper Citation Record · LEDGER

A Deep State Space Model for Rainfall-Runoff Simulations

As of 10 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations 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 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

56 of 56 outbound references displayed

  • verified exact2
  • verified fuzzy41
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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

Resolution
unresolved
no resolver link, observed 2026-08-10T14:47:45.440923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:47:45.440923Z digest=sha256:ff459670c52d3a29fa577b2d131fced9259c1583d9b0f7f87b0a4eb2c19ce5d6

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.447516Z digest=sha256:7e935f4f058e95334091dc6d123930912445754c90a3c75359abe6b225a2d352

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.453130Z digest=sha256:172692dee1fd4689afdf0f7fe608b34554d31c436f7a74aff78cbc36bef4de0f

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.458285Z digest=sha256:f4bb4863be30a5588fe5581ac8b9653b5edf80473d5008ec76bf562a0c129ba0

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:47:46.532313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.462913Z digest=sha256:758ce55661b6579ecd79a9e499799e424987603fa8989038c5d6fdbc3f17449b

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.467514Z digest=sha256:327840736d8457d68f596334af12f154186c23e15bd753a6f86738ec41ad239d

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.472164Z digest=sha256:83aa2cd9950dbe33960f2970ced5b3c81bd294153a4cd0880f113df4b84b1b0e

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.477280Z digest=sha256:a57af9c7b17b606fae94bf77c89988ae070f6500e98a5916cf296f779e7e6c33

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.481835Z digest=sha256:c5dcd23b9ee82c7ee61bc52c10f7fffea1e95f9f91b28ffcc5d65bd667c971d2

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.486457Z digest=sha256:4de6e04b7884c37a10becefadc7171a789d55f55b40c1f61772d189f7c117a76

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.491357Z digest=sha256:ad7e7dce44f1b64468d57f8cad9dd09e98730d6f723892615822de761f6b69d5

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

Resolution
unresolved
no resolver link, observed 2026-08-10T14:47:45.495967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:47:45.495967Z digest=sha256:de0e8d18c79477dab1f0f8fe8162baf9a5ab49e5980ec54373e92a232e6078f4

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.500698Z digest=sha256:55bc3579ffee6d2629c70ab1fce4a10f1cb5627c860af692f9ed966ef1c7adf9

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.505478Z digest=sha256:6bbd14236d2b145751a1c234a6413da3777011d8d2e24b79b7ced8b74338c5c6

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.509795Z digest=sha256:937075fc531c36e825a0b0089ed24fafb9310d3a8b7c8d9908c67dec15273377

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.513877Z digest=sha256:a0b3144d4835432e6952589ea773ff842773cf04da457b6fde1c15dc37884b4c

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

Resolution
unresolved
no resolver link, observed 2026-08-10T14:47:45.518004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:47:45.518004Z digest=sha256:73ae2e578395cb21d3fb38f9cece8dbc0d3c671926561a9ae7ea520cb9024d49

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

Resolution
unresolved
no resolver link, observed 2026-08-10T14:47:45.523351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:47:45.523351Z digest=sha256:f574fc30e0b61bd5a04eaa79600278ae5997264f97d7ce651e711e122dee81a7

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.528279Z digest=sha256:d112188a0cc58e0caaf29fb2a68368cf8d2c65aeba74b58aed2ef6cac1b8071d

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.532965Z digest=sha256:228b582c61cb24f64d0d8a83af86c6537850f52266953f2cf571e6662de8573c

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.537764Z digest=sha256:35a4884514c8de2f02f49cd74a7ac0a3642bc258a34bfb0c08898c0da40b7eb1

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.542437Z digest=sha256:bca53ef26db3d46b0aae1518db746cf64192201b7a4c6fffbbafb55675d2e75b

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

Resolution
unresolved
no resolver link, observed 2026-08-10T14:47:45.546825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:47:45.546825Z digest=sha256:bcb66316dc66b1da9e791eded6565d7d06a994a7d829e5944b4b548c2234e05a

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:47:46.306472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.551108Z digest=sha256:87daf1d0ec0ed88de615d3ccdb48024a78aa16a4f1cc775b530b5f355491a7d7

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.555167Z digest=sha256:b9da888db32db5fe45731fa2cf4d6ed91e62bed191a9fe84df559642b5710d74

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.567092Z digest=sha256:22235d2558eb12e985f19b73145d73d0607040a76bd4963de2a302a878943fa7

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.571831Z digest=sha256:d024bb62e1a2b8157e0f569402ad3fa4a756d91770cb5b14c83432a617340b87

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.576639Z digest=sha256:6de8cd851cca579c764f4807510ac49117cfe6f286c37901353cc376b9352e52

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.581013Z digest=sha256:b1848a0dd6f8dc19e162d48e2c9aa4faef0cf88fe89d7a2b6db608849389fd78

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.585426Z digest=sha256:eafb74392ce35d164e68b0c966b81bd0aafd5c58560163ddcc050a5bc94710e9

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

Resolution
unresolved
no resolver link, observed 2026-08-10T14:47:45.590382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:47:45.590382Z digest=sha256:3e29490d4e6e04e6d484aef3d4efaf5a519cdf5ffe5c0ad36a757929e3abce3e

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.596052Z digest=sha256:256ea61f2a03f73ae7a3dd7b8ceda477580e2625f42a6bc01282ff4accce6627

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.600933Z digest=sha256:27851969c32fd9a1a7f09f419d4aab1bd870f561e44f8063bc9de60d5452f47a

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:47:46.176787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.605815Z digest=sha256:56c8279e091a13555246ed3d7e84cbcca0fd5c7f233fc35e98ee8a6bc5ead866

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.611221Z digest=sha256:66aef790d1400a5b4f0a56b302749a625b8022058cade13e38b395b62b9915c3

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

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:47:46.147625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.617097Z digest=sha256:a6b04841cc1315407d7a3bbb6ee0115e33c24b6b3b68ca6efe71a8219205b09c

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

Resolution
unresolved
no resolver link, observed 2026-08-10T14:47:45.621742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:47:45.621742Z digest=sha256:6b5659cca4a60c672bcf4cea266ce3da15d4b96bc3c8f052090f7154859d93c2

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

Resolution
unresolved
no resolver link, observed 2026-08-10T14:47:45.626839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:47:45.626839Z digest=sha256:0a079d1f5c19c5f3fa5ca96fe96f7808e4e57f8bf60155f2f3fa9458072c4743

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.631572Z digest=sha256:c7fd9f02edc2f6af7e35c926ccc9ae2202adb19278205eaa69849a89e60580af

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.635955Z digest=sha256:066aff372f89f8bac05a6cfa5766eaeb0f5d9ab00fb25a2f654223d0dc3ebfcf

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.640583Z digest=sha256:00ec86d7383930f08450facb0120c92f15e8fbf15c6f48ca063459b0f5b42093

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.644762Z digest=sha256:84a07ed89e87d7330e1200341b0465b83d2632a6e8d339eb1938bf7f7c097ffe

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.649323Z digest=sha256:55a2501ad8514264a77ac99c69c1bd6f182d0520779b69d2e30b1e7c2d7449be

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.654689Z digest=sha256:8e6cb52a1c19f18dd317c492df6a8ff061657c57d0636b7c0a6147def8dda30c

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.

source=arxiv_source observed=2026-08-10T14:47:45.659626Z digest=sha256:203d895e0f45e970b90c63852a7fc3c5648c96b2e8faf2cecb0dfe611fb7b315

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.664681Z digest=sha256:5c26ff702d6fc185d56654bd0e753e4cebf4924b88bf127bca425eff0b32b8f4

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.669486Z digest=sha256:bd3153bb57b772e7a870bca81755557a39fd5065e94a65998723628c4ffbdd95

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.675691Z digest=sha256:908bd1a4707aa69789e40370046b4f7c1144e7b0c8c9355a13ffa6bee2a4eb9e

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.680722Z digest=sha256:d69199cbb4ec3f10404e306cefa15ff9b9f4fad7b5c6bf46ab37db6be36f3d49

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.685883Z digest=sha256:6c277e8d47bb87e1f0ee8804e1e130c525458bb7f05ab8dfe78aaaafb2feed2d

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.691550Z digest=sha256:6421c7f267dbb8c986e02fe009f6fee4b2f993a6eef282942f251a713561040c

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.697393Z digest=sha256:0b2510bcee2f3b073bbdbb0bb1bcef78a5a0016856dab41d4a6e8773490a964e

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T14:47:45.702244Z digest=sha256:84cbf2c88e37fe68b04de8fefe1ae96000e32b541f9f7d4f6ee94538c2a32fc5

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:47:45.706942Z digest=sha256:034eac8b07ca30b8187daa35a99c27f468456931811d23a580f47f629d958003

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:47:45.711871Z digest=sha256:d7c41677b353e7672f82ad8a9e9eb02e5a61522403e31f270ed7f41f6b168f92

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:47:45.717499Z digest=sha256:8d7c4834e6f43c45a1920794dbb16292ff36b2d88f5df54de400d431e962aef5

Pith citing papers

No inbound Pith citation observations are available.