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Paper Citation Record · LEDGER

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection

As of 17 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2608.02343.

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

pith.paper-citation-record.v1
2608.02343 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T09:06:06.790458Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

50 of 50 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved50
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b8093e74-6d0f-4b87-82ab-cf10dffca8f1 · outbound

This paper cites Proceedings of the 33rd International Conference on Neural Information Processing Systems.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Proceedings of the 33rd International Conference on Neural Information Processing Systems

Reference 1

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source=arxiv_source observed=2026-08-04T09:06:00.906824Z digest=sha256:c823f695259a4c49723a1028c917eb6b46bbf6669fdf63760ffd8339b539ed02

Observation 7b9ae549-695b-4977-a0cd-6fc75c5940b7 · outbound

This paper cites Deep Reinforcement Learning for Inventory Networks: Toward Reliable Policy Optimization.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Deep Reinforcement Learning for Inventory Networks: Toward Reliable Policy Optimization

Reference 2

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source=arxiv_source observed=2026-08-04T09:06:00.999288Z digest=sha256:1b0d9347212dd6e357d97415b57cb1548f407f9a8bbc3edbd3d56a35b625322b

Observation 74e782ff-b9b7-4720-bd78-cb6fb3f852b8 · outbound

This paper cites Proceedings of the 34th International Conference on Machine Learning, volume 70 of PMLR, 136--145.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Proceedings of the 34th International Conference on Machine Learning, volume 70 of PMLR, 136--145

Reference 3

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source=arxiv_source observed=2026-08-04T09:06:01.131019Z digest=sha256:2575060b021efdc63301186f1b35037f100e348f8cd08d492a5d847bb9fe3971

Observation 8360427c-276c-43a8-9bf5-614f5b28e2f2 · outbound

This paper cites an unresolved cited work.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Unresolved cited work

Reference 4

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source=arxiv_source observed=2026-08-04T09:06:01.301219Z digest=sha256:cb270bda93b3161fb7c528839f766f235754e450f7fe5aa4d1863beec1a50d23

Observation ba871fa3-8c5f-4f00-b968-8bab59d35760 · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 5

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source=arxiv_source observed=2026-08-04T09:06:01.500555Z digest=sha256:484d293eef5aa680ea2158dd5c0e65093435ce49a93adf4b6eedb1d89cb25897

Observation 368c59cb-88f4-429c-b087-47f1a3afa976 · outbound

This paper cites Journal of Machine Learning Research 21(35):1--69.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Journal of Machine Learning Research 21(35):1--69

Reference 6

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source=arxiv_source observed=2026-08-04T09:06:01.672530Z digest=sha256:0ce437c39ed3ee1e51bfe123d2bc7a2cd25369649f17f3f31e6bf86e5982edc0

Observation f1ab5c99-6ebe-4b10-8c4d-879a255accbe · outbound

This paper cites INFORMS Journal on Computing 35(6):1308--1328.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection INFORMS Journal on Computing 35(6):1308--1328

Reference 7

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source=arxiv_source observed=2026-08-04T09:06:01.826749Z digest=sha256:0803d48924f256394019861cba57ca00ff9308a7677cab8594566acbe204ef4c

Observation da0a52b8-797b-45f5-b091-584fb38f0797 · outbound

This paper cites an unresolved cited work.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Unresolved cited work

Reference 8

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source=arxiv_source observed=2026-08-04T09:06:02.005277Z digest=sha256:1088734ad39bf85b677f13c060c897e9f57b68f008e86edaae5f15178631b06e

Observation 8df9d9a9-63ff-455b-aaab-96c838f981c3 · outbound

This paper cites Quantitative Finance 19(8):1271--1291.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Quantitative Finance 19(8):1271--1291

Reference 9

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source=arxiv_source observed=2026-08-04T09:06:02.144264Z digest=sha256:2fb9b8c100396e14d7e2690b6b12e2ffac1b2112f7ca6eb9acebff2d24ab9a9e

Observation 618de7e7-6855-4488-8e3d-f90a15ec2533 · outbound

This paper cites Differentiable Discrete Event Simulation for Queuing Network Control.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Differentiable Discrete Event Simulation for Queuing Network Control

Reference 10

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source=arxiv_source observed=2026-08-04T09:06:02.246021Z digest=sha256:9f582aa15dadab4b57c582c2d6afba07e494bac1a18a6c30a07c10b0c5ae9f1f

Observation cfe30cd5-55a5-4091-ab74-0b1e374b28d4 · outbound

This paper cites Management S cience 6(4):475--490.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Management S cience 6(4):475--490

Reference 11

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Observation 7361252c-e1d7-4a1f-93e1-fcc89df01781 · outbound

This paper cites Safe Exploration in Continuous Action Spaces.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Safe Exploration in Continuous Action Spaces

Reference 12

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Observation 98aa7beb-1bfb-4bb6-b094-33cc033dc44b · outbound

This paper cites de Kok A, Graves S, eds., Design and Analysis of Supply Chains, 597--675, Handbooks in Operations Research and Management Science (North-Holland Publishing Company).

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection de Kok A, Graves S, eds., Design and Analysis of Supply Chains, 597--675, Handbooks in Operations Research and Management Science (North-Holland Publishing Company)

Reference 13

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Observation 5a7928ca-090e-44fa-87cc-47ef8e9cec7d · outbound

This paper cites European Journal of Operational Research 269(3):955--983.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection European Journal of Operational Research 269(3):955--983

Reference 14

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source=arxiv_source observed=2026-08-04T09:06:02.851296Z digest=sha256:5db32dd97662a7c37ac7ad830497f12319fa55c7e1331341769adbcb4f0eefdb

Observation 064d533e-c9a0-4bd4-bde0-01258547ce18 · outbound

This paper cites International Conference on Learning Representations (ICLR).

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection International Conference on Learning Representations (ICLR)

Reference 15

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source=arxiv_source observed=2026-08-04T09:06:02.995154Z digest=sha256:7ea83067bda38f3b58855b482ab3232dfc81decf18dbae01ae28c63158a13963

Observation 2ff4be71-1c0b-4d2c-8600-313f7092b230 · outbound

This paper cites Journal of Process Control 116:80--92.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Journal of Process Control 116:80--92

Reference 16

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source=arxiv_source observed=2026-08-04T09:06:03.105546Z digest=sha256:ff747e0fdfdb21289caa04b32172456598174fa8f7694775f060eaf2a177b125

Observation 245a7c15-5c15-4cd3-97e0-1cf48a254ff0 · outbound

This paper cites Neural Coordination and Capacity Control for Inventory Management.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Neural Coordination and Capacity Control for Inventory Management

Reference 17

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source=arxiv_source observed=2026-08-04T09:06:03.200845Z digest=sha256:0d4e9a8637143ca4936ce0cc4a970adc434049127019f379c67b1d57294a484d

Observation 488db0e9-8ebf-4f1a-b1c0-cab6995de980 · outbound

This paper cites Management Science 68(1):9--26.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Management Science 68(1):9--26

Reference 18

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source=arxiv_source observed=2026-08-04T09:06:03.321617Z digest=sha256:63060957536cda331f9e6811829991c72230fde3818bee6d777946d9546ab86e

Observation f97c01ad-37ea-408c-a8aa-1e1f88d70298 · outbound

This paper cites International Journal of Production Economics 288:109687.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection International Journal of Production Economics 288:109687

Reference 19

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Observation 4491711e-6c56-4afe-bfac-033b9d0022b8 · outbound

This paper cites Manufacturing & Service Operations Management 24(3):1349--1368.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Manufacturing & Service Operations Management 24(3):1349--1368

Reference 20

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Observation 17b6c8de-1848-45b6-aaf3-98d21975140e · outbound

This paper cites Cohen MC, Dai T, eds., AI in Supply Chains: Perspectives from Global Thought Leaders, 137--148 (Cham: Springer Nature Switzerland).

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Cohen MC, Dai T, eds., AI in Supply Chains: Perspectives from Global Thought Leaders, 137--148 (Cham: Springer Nature Switzerland)

Reference 21

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source=arxiv_source observed=2026-08-04T09:06:03.627795Z digest=sha256:c49e9907fc41c963d03eac321b05c208da3630446e40ffca2fc7ae6c6947dd67

Observation a5bdff91-2026-4d3e-a700-c9692fd8d524 · outbound

This paper cites Management Science 41(2):263--281.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Management Science 41(2):263--281

Reference 22

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source=arxiv_source observed=2026-08-04T09:06:03.711490Z digest=sha256:7ab9013a040235e6289b167abe2b176667620215b5b1b51b169007871a184a6e

Observation 6c7f1c94-73ff-4a25-8b95-67dbbe98fb26 · outbound

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Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Unresolved cited work

Reference 23

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Observation 5a23e01a-19cc-4c39-b71d-69c7f7a468a6 · outbound

This paper cites Manufacturing & Service Operations Management 27(2):369--388.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Manufacturing & Service Operations Management 27(2):369--388

Reference 24

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Observation 760a8874-caea-42f0-881a-478bb23eee32 · outbound

This paper cites The 39th Annual Conference on Neural Information Processing Systems.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection The 39th Annual Conference on Neural Information Processing Systems

Reference 25

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source=arxiv_source observed=2026-08-04T09:06:03.904194Z digest=sha256:dc843600d7a8d0a08722530e63f452410a38237f7d3f4b0be2e847b470d117ac

Observation 918a6a1f-0497-4161-a747-1aa5c764dbe9 · outbound

This paper cites Manufacturing & Service Operations Management 18(4):570--584.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Manufacturing & Service Operations Management 18(4):570--584

Reference 26

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source=arxiv_source observed=2026-08-04T09:06:04.019341Z digest=sha256:cffa019e8a0742cc01331ca60a5de7e9a51498e9ea5be77808fefb10a80c6749

Observation 438a9ca0-a7d1-458b-9a8b-010b5453e131 · outbound

This paper cites Management Science 33(3):409--418.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Management Science 33(3):409--418

Reference 27

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Observation 29d978da-3822-4b27-a98d-56230fcad42a · outbound

This paper cites International Journal of Production Economics 267:109088.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection International Journal of Production Economics 267:109088

Reference 28

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Observation a8479532-2549-4d50-a27d-d0e5cccfde29 · outbound

This paper cites International Conference on Learning Representations (ICLR).

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection International Conference on Learning Representations (ICLR)

Reference 29

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source=arxiv_source observed=2026-08-04T09:06:04.428140Z digest=sha256:24705a71b5331fe2e2d5a0e24edde2a306757ea96b42afda662cb34ed89e2bc3

Observation 2ff09da0-e64e-4563-97e6-d98726f7f2bd · outbound

This paper cites arXiv preprint arXiv:2507.14446.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection arXiv preprint arXiv:2507.14446

Reference 30

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source=arxiv_source observed=2026-08-04T09:06:04.611363Z digest=sha256:6fc5082a39fe371311bd2d7c3ddf020a1db4cc79346c96c8db9c43ae9efb5b81

Observation b358478a-4bc7-49ef-b8ca-d495a9f5bfc9 · outbound

This paper cites human buyers: A study of alibaba’s inventory replenishment system.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection human buyers: A study of alibaba’s inventory replenishment system

Reference 31

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Observation 36287bc7-9bde-43cf-b43e-d2a1884e3b00 · outbound

This paper cites Deep Inventory Management.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Deep Inventory Management

Reference 32

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source=arxiv_source observed=2026-08-04T09:06:04.860504Z digest=sha256:d31efd45af8a0aa429408a2728ac57948da706fb8ed57d6e8a346e99302903a5

Observation 935e3e0d-ad56-431c-8023-99d00e37a8d6 · outbound

This paper cites European Journal of Operational Research 329(2):447--459.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection European Journal of Operational Research 329(2):447--459

Reference 33

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Observation 6780085a-a9a1-4edd-b6ba-4b071b67207b · outbound

This paper cites Journal of Artificial Intelligence Research 80:1623--1701.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Journal of Artificial Intelligence Research 80:1623--1701

Reference 34

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source=arxiv_source observed=2026-08-04T09:06:05.115835Z digest=sha256:62277d8fff964fb6b0891ace1d130807c2728e885d319bab3f6dfb05ebfab5d5

Observation 8a81e1aa-e891-4e63-bca5-556cdb1c0fef · outbound

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Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Unresolved cited work

Reference 35

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source=arxiv_source observed=2026-08-04T09:06:05.200735Z digest=sha256:690373341bf8033109056d3e977aff96cc06f93a3fe24c9319127322a6ddb91f

Observation f9b2c0b7-508b-44f7-a7c4-3d34c8a9cde8 · outbound

This paper cites Manufacturing & Service Operations Management 24(1):285--304.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Manufacturing & Service Operations Management 24(1):285--304

Reference 36

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Observation cb1c7f85-0684-42c1-b774-0bc97b08a49d · outbound

This paper cites Proceedings of the 33rd International Conference on Neural Information Processing Systems.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Proceedings of the 33rd International Conference on Neural Information Processing Systems

Reference 37

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Observation 84d05e5e-08c6-45d5-80ca-0dfe11d9e9f3 · outbound

This paper cites Proceedings of the 38th International Conference on Machine Learning, volume 139 of PMLR, 8443--8453.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Proceedings of the 38th International Conference on Machine Learning, volume 139 of PMLR, 8443--8453

Reference 38

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source=arxiv_source observed=2026-08-04T09:06:05.521922Z digest=sha256:068d29c9c28edd5652c47dec62890e74b9ebd0f70017a4d28a01df132c7f9f56

Observation 2df7b164-9f8e-4011-81e4-d070dc38a045 · outbound

This paper cites Management Science 69(2):759--773.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Management Science 69(2):759--773

Reference 39

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source=arxiv_source observed=2026-08-04T09:06:05.602698Z digest=sha256:4fca11250cf224a72bf4c2fc907958e780485cc45d38f39c5236f8e062568228

Observation 0cecd931-0a13-4861-871b-943b56c91d73 · outbound

This paper cites Manufacturing & Service Operations Management 22(1):36--46.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Manufacturing & Service Operations Management 22(1):36--46

Reference 40

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source=arxiv_source observed=2026-08-04T09:06:05.671995Z digest=sha256:96dc3801353b3023ad637010939e6764402295519beea335a35ca2ca9a9c4412

Observation 16c8c730-e0ac-4f5a-b320-2d2ce140e72e · outbound

This paper cites an unresolved cited work.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Unresolved cited work

Reference 41

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source=arxiv_source observed=2026-08-04T09:06:05.800510Z digest=sha256:f90a7e02f8e95ec2b68af02604ff96188de201797b664ee9218995ab7530f914

Observation ec4f15dc-fe83-403e-a651-5889f51af42f · outbound

This paper cites Management Science 42(5):738--757.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Management Science 42(5):738--757

Reference 42

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source=arxiv_source observed=2026-08-04T09:06:05.884488Z digest=sha256:c460d7f350a3996ffe4097456e892903c84d4fd95a0e256b375777653e271a2b

Observation a46962c5-00d4-4782-8dc2-cc8f7fb724b3 · outbound

This paper cites Production and Operations Management 30(2):475--493.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Production and Operations Management 30(2):475--493

Reference 43

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source=arxiv_source observed=2026-08-04T09:06:05.943396Z digest=sha256:348a066518483bddadfea3ed0860a59c734c68c95430e1c13c332fb5a62c2d32

Observation 266be7d7-90fe-42df-9ea2-977077bd0a73 · outbound

This paper cites International Journal of Production Economics 49(2):157--174.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection International Journal of Production Economics 49(2):157--174

Reference 44

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source=arxiv_source observed=2026-08-04T09:06:06.085800Z digest=sha256:3282b2bf94090510b42b3f45f417889075be6e389b73d434237c267f973a0620

Observation 6827334c-c1e0-40c1-b57e-71501172e136 · outbound

This paper cites https://www.isir2025.com/research-challenge/information.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection https://www.isir2025.com/research-challenge/information

Reference 45

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source=arxiv_source observed=2026-08-04T09:06:06.203233Z digest=sha256:53218c50444482b619298e78e5ad7368179abd283d70f1127c32fec8898814d8

Observation 345d96ba-cfae-4809-b82f-f1ce96a941e3 · outbound

This paper cites SSRN 4843271.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection SSRN 4843271

Reference 46

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source=arxiv_source observed=2026-08-04T09:06:06.276267Z digest=sha256:b92a56e8a4af31828a45039514c83402b434e2dd0261524441d3fc7ad7525f66

Observation 7b4e8a57-bf14-400c-bb04-1ee947e78d83 · outbound

This paper cites an unresolved cited work.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Unresolved cited work

Reference 47

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source=arxiv_source observed=2026-08-04T09:06:06.419669Z digest=sha256:e417a2c76de4b51d308a5a50dddd8c1a6275f27f03a22d7526e41bd0d7c59ad9

Observation f164f165-6825-45d3-9ee6-b65b1b0508a9 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence 33(01):1658--1665.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Proceedings of the AAAI Conference on Artificial Intelligence 33(01):1658--1665

Reference 48

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source=arxiv_source observed=2026-08-04T09:06:06.534255Z digest=sha256:51acffa83b0728278bacb1e2384397a6bf7511e0b6cf3eb953224c752ecb6238

Observation e54715b7-65f6-4aff-a657-3fdb7569bd79 · outbound

This paper cites Machine Learning 8(3-4):229--256.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection Machine Learning 8(3-4):229--256

Reference 49

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source=arxiv_source observed=2026-08-04T09:06:06.672185Z digest=sha256:1b88e6b76a30d2ecc80a85f9db1764ece8b2a18673d2de6a35f5db39fb2ca375

Observation 78a640fa-33e0-45e1-a870-48c90874956f · outbound

This paper cites arXiv preprint arXiv:2603.19621.

Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection arXiv preprint arXiv:2603.19621

Reference 50

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source=arxiv_source observed=2026-08-04T09:06:06.790458Z digest=sha256:08952804636b656939d077e931b63f7fa5087126db95a694fa788d16765a3ad2

Pith citing papers

No inbound Pith citation observations are available.