Differentiable Causal Discovery For Latent Hierarchical Causal Models | Paper Citation Record

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This paper cites Identification of partially observed linear causal models: Graphical conditions for the non-gaussian and heterogeneous cases.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Identification of partially observed linear causal models: Graphical conditions for the non-gaussian and heterogeneous cases

Reference 1

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Observation 012f46a9-701c-40dd-b48a-f5a6c9bc678d · outbound

This paper cites The decamfounder: nonlinear causal discovery in the presence of hidden variables.

Differentiable Causal Discovery For Latent Hierarchical Causal Models The decamfounder: nonlinear causal discovery in the presence of hidden variables

Reference 2

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Observation 77300d2b-b744-4443-8c73-bb9b3b848ab5 · outbound

This paper cites Recursive causal structure learning in the presence of latent variables and selection bias.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Recursive causal structure learning in the presence of latent variables and selection bias

Reference 3

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This paper cites Learning linear bayesian networks with latent variables.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Learning linear bayesian networks with latent variables

Reference 4

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This paper cites Invariant Risk Minimization.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Invariant Risk Minimization

Reference 5

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This paper cites Mutual information neural estimation.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Mutual information neural estimation

Reference 6

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Observation 75c0c07a-150c-4973-bdbf-e812b8ca5034 · outbound

This paper cites Deconfounded Score Method: Scoring DAGs with Dense Unobserved Confounding.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Deconfounded Score Method: Scoring DAGs with Dense Unobserved Confounding

Reference 7

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Observation fd1e50ce-62cf-4aa0-ac5d-2a1857dd70a7 · outbound

This paper cites Differentiable causal discovery under unmeasured confounding.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Differentiable causal discovery under unmeasured confounding

Reference 8

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Observation 0e9fecf1-6435-4337-90e1-c601fcbbb956 · outbound

This paper cites Weakly supervised causal representation learning.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Weakly supervised causal representation learning

Reference 9

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Observation 938197e3-9e62-4008-9e16-623e878d80e6 · outbound

This paper cites Differentiable causal discovery from interventional data.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Differentiable causal discovery from interventional data

Reference 10

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Observation e7cdba90-feeb-4db8-a90d-2eb1d40e676c · outbound

This paper cites Identification of linear latent variable model with arbitrary distribution.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Identification of linear latent variable model with arbitrary distribution

Reference 11

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Observation dfe5da31-9236-4d2c-9c47-797dd1800190 · outbound

This paper cites Optimal structure identification with greedy search.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Optimal structure identification with greedy search

Reference 12

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Observation cf055842-52f5-49f8-b8e4-ba50c371d30e · outbound

This paper cites Large-sample learning of bayesian networks is np-hard.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Large-sample learning of bayesian networks is np-hard

Reference 13

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Observation abe6898d-cc6f-460f-b010-160cde5b021b · outbound

This paper cites Learning latent tree graphical models.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Learning latent tree graphical models

Reference 14

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Observation b294cada-0147-4617-9d42-d539ab654a32 · outbound

This paper cites Learning Sparse Causal Models is not NP-hard.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Learning Sparse Causal Models is not NP-hard

Reference 15

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Observation 434f4fc0-fa59-4a41-91fe-77407de925af · outbound

This paper cites Learning high-dimensional directed acyclic graphs with latent and selection variables.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Learning high-dimensional directed acyclic graphs with latent and selection variables

Reference 16

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Observation dc43fb5f-7257-4a41-beab-31fc96928002 · outbound

This paper cites Learning the causal structure of copula models with latent variables.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Learning the causal structure of copula models with latent variables

Reference 17

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Observation 97e59d06-c3c5-44c3-a3b7-59fd6b605437 · outbound

This paper cites A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables.

Differentiable Causal Discovery For Latent Hierarchical Causal Models A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables

Reference 18

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Observation 9da49251-6b81-48d1-bb44-70b29d38e07e · outbound

This paper cites Asymptotic evaluation of certain markov process expectations for large time.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Asymptotic evaluation of certain markov process expectations for large time

Reference 19

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Observation 7bf71f34-4ac4-4da6-add8-49df096f7fa7 · outbound

This paper cites Marginal likelihood and model selection for gaussian latent tree and forest models.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Marginal likelihood and model selection for gaussian latent tree and forest models

Reference 20

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Observation c95497b1-8bfc-4323-a83d-593badb2b717 · outbound

This paper cites Unsupervised learning of transcriptional regulatory networks via latent tree graphical models.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Unsupervised learning of transcriptional regulatory networks via latent tree graphical models

Reference 21

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Observation 4332713d-9171-4846-a1ba-c21464311657 · outbound

This paper cites Bayesian pyramids: Identifiable multilayer discrete latent structure models for discrete data.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Bayesian pyramids: Identifiable multilayer discrete latent structure models for discrete data

Reference 22

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Observation 9dd7e2a0-fb2d-491b-8528-beded5b91862 · outbound

This paper cites Variational autoencoders with jointly optimized latent dependency structure.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Variational autoencoders with jointly optimized latent dependency structure

Reference 23

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Observation fcf0862d-fafa-4e98-a155-727bfd8d90be · outbound

This paper cites beta-vae: Learning basic visual concepts with a constrained variational framework.

Differentiable Causal Discovery For Latent Hierarchical Causal Models beta-vae: Learning basic visual concepts with a constrained variational framework

Reference 24

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Observation 76a0f8f9-37cc-4509-9c6a-ffdc7cd0f27e · outbound

This paper cites SCAN: Learning Hierarchical Compositional Visual Concepts.

Differentiable Causal Discovery For Latent Hierarchical Causal Models SCAN: Learning Hierarchical Compositional Visual Concepts

Reference 25

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Observation cfc03e74-8c47-4904-a953-cee0a31bd658 · outbound

This paper cites Latent hierarchical causal structure discovery with rank constraints.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Latent hierarchical causal structure discovery with rank constraints

Reference 26

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Observation d4f3eb9a-1930-4a45-9c7b-4ffc28ef9496 · outbound

This paper cites Nonlinear ica using auxiliary variables and generalized contrastive learning.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Nonlinear ica using auxiliary variables and generalized contrastive learning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:16:37.938753Z

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Observation 917e6a13-a531-4cc8-add5-e51b502e50f2 · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Categorical Reparameterization with Gumbel-Softmax

Reference 28

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Observation 8a600d89-03c4-4b3e-bee9-0d9dc20130c5 · outbound

This paper cites Auto-Encoding Variational Bayes.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Auto-Encoding Variational Bayes

Reference 29

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Observation 160d8f09-abe8-4140-96b6-4a5cb23002b4 · outbound

This paper cites Learning latent causal graphs via mixture oracles.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Learning latent causal graphs via mixture oracles

Reference 30

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Observation ebf9fd0d-51ec-4f13-b6c6-4378bfbe364b · outbound

This paper cites Identification of nonlinear latent hierarchical models.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Identification of nonlinear latent hierarchical models

Reference 31

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Observation 90e66881-66d6-4dd4-ba94-8c133457aa37 · outbound

This paper cites Learning Discrete Concepts in Latent Hierarchical Models.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Learning Discrete Concepts in Latent Hierarchical Models

Reference 32

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Observation bd7720ce-668b-4444-a461-1345a9d710ad · outbound

This paper cites Causal clustering for 1-factor measurement models.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Causal clustering for 1-factor measurement models

Reference 33

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Observation ecc2346e-fb4c-4233-bc49-f55e487986f0 · outbound

This paper cites Mnist handwritten digit database.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Mnist handwritten digit database

Reference 34

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Observation 44f039c7-62b9-456f-acb1-1cf596a7ff8b · outbound

This paper cites Causal discovery from observational and interventional data across multiple environments.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Causal discovery from observational and interventional data across multiple environments

Reference 35

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Observation 699b7902-0cc5-449d-b85f-a6300e16f0a3 · outbound

This paper cites Deep learning face attributes in the wild.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Deep learning face attributes in the wild

Reference 36

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This paper cites Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior (Extended Version).

Differentiable Causal Discovery For Latent Hierarchical Causal Models Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior (Extended Version)

Reference 37

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Observation c5613b95-097c-4d1e-ad70-55f3f0a38940 · outbound

This paper cites Stable Differentiable Causal Discovery.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Stable Differentiable Causal Discovery

Reference 38

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Observation 38bfdfe1-c4d7-4554-bdbe-7fb9df57b5cb · outbound

This paper cites Masked gradient-based causal structure learning.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Masked gradient-based causal structure learning

Reference 39

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Observation ca3e783a-258e-4176-bbd6-6306b8df6599 · outbound

This paper cites Structure learning with continuous optimization: A sober look and beyond.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Structure learning with continuous optimization: A sober look and beyond

Reference 40

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Observation 747b401e-1afb-44fd-baec-ab18f78c9612 · outbound

This paper cites Comprehensive Review and Empirical Evaluation of Causal Discovery Algorithms for Numerical Data.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Comprehensive Review and Empirical Evaluation of Causal Discovery Algorithms for Numerical Data

Reference 41

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Observation b1115a40-b2ca-417f-9364-031ddc70fd71 · outbound

This paper cites Causes of severe pneumonia requiring hospital admission in children without hiv infection from africa and asia: the perch multi-country case-control study.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Causes of severe pneumonia requiring hospital admission in children without hiv infection from africa and asia: the perch multi-country case-control study

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:16:37.845595Z

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Observation 5ef3f880-e2e7-47dc-ac48-989e1d09d9b8 · outbound

This paper cites Probabilistic reasoning in intelligent systems; network of plausible inference.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Probabilistic reasoning in intelligent systems; network of plausible inference

Reference 43

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Observation bd32ee90-e99b-4d26-a428-4b110e1fa087 · outbound

This paper cites Models, reasoning and inference.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Models, reasoning and inference

Reference 44

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Observation d18d1808-42ea-4230-89f1-db22c0cf5ce9 · outbound

This paper cites Beware of the simulated dag! causal discovery benchmarks may be easy to game.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Beware of the simulated dag! causal discovery benchmarks may be easy to game

Reference 45

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Observation ba7d1b21-e7e7-40a5-a095-470ea384c1b1 · outbound

This paper cites Toward causal representation learning.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Toward causal representation learning

Reference 46

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Observation 55622ad2-1b1c-4c4e-8c08-3b6344c75e1a · outbound

This paper cites Learning large dags is harder than you think: Many losses are minimal for the wrong dag.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Learning large dags is harder than you think: Many losses are minimal for the wrong dag

Reference 47

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Observation c35e7a27-045d-48c5-bb3b-5ccbdf604c17 · outbound

This paper cites Nodags-flow: Nonlinear cyclic causal structure learning.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Nodags-flow: Nonlinear cyclic causal structure learning

Reference 48

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Observation fafeb780-8a1f-4f87-884e-34fdf67eae7b · outbound

This paper cites Estimation of linear non-gaussian acyclic models for latent factors.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Estimation of linear non-gaussian acyclic models for latent factors

Reference 49

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Observation 89a863e5-dbc3-45c0-b394-59e96c5962f5 · outbound

This paper cites Learning the structure of linear latent variable models.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Learning the structure of linear latent variable models

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:16:37.749382Z

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Observation 1cacd245-7f76-49aa-b420-caf885674b84 · outbound

This paper cites Introduction to causal inference.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Introduction to causal inference

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:16:37.738241Z

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Observation ef050505-b912-4990-aeaa-3af34e4d25b2 · outbound

This paper cites Causation, prediction, and search.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Causation, prediction, and search

Reference 52

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Observation 9cbdd534-68f0-4d9f-9295-0978da40e226 · outbound

This paper cites Unpaired multi-domain causal representation learning.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Unpaired multi-domain causal representation learning

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:16:37.718919Z

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Observation 2703f543-8d45-468c-8ab1-489431bcd540 · outbound

This paper cites Learning Latent Structural Causal Models.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Learning Latent Structural Causal Models

Reference 54

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Observation dadec23f-9ad5-4c2c-8219-02ddf5940ac0 · outbound

This paper cites Nvae: A deep hierarchical variational autoencoder.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Nvae: A deep hierarchical variational autoencoder

Reference 55

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Observation 346355e9-af44-483e-842b-aceb15894180 · outbound

This paper cites Hierarchical Causal Models.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Hierarchical Causal Models

Reference 56

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Observation 1df2bb25-caaa-435d-9c9e-72a0034b5879 · outbound

This paper cites Generalized independent noise condition for estimating latent variable causal graphs.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Generalized independent noise condition for estimating latent variable causal graphs

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:16:37.697915Z

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Observation 3c19c647-5dd2-4c8c-8050-d1644da61eca · outbound

This paper cites Identification of linear non-gaussian latent hierarchical structure.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Identification of linear non-gaussian latent hierarchical structure

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:16:37.685682Z

Source-reported events for the cited work

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Observation 216df78d-63ab-46ec-b140-5b9a5dab9a64 · outbound

This paper cites Causalvae: Disentangled representation learning via neural structural causal models.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Causalvae: Disentangled representation learning via neural structural causal models

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-12T10:16:37.318510Z

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Observation 7bf64de8-0bbd-4d44-b2eb-1f9716e35d3c · outbound

This paper cites Dag-gnn: Dag structure learning with graph neural networks.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Dag-gnn: Dag structure learning with graph neural networks

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:16:37.666100Z

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 8b0eecf4-fa98-46be-ac93-b137e670c122 · outbound

This paper cites Causal discovery with multi-domain lingam for latent factors.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Causal discovery with multi-domain lingam for latent factors

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:16:37.652945Z

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Observation 32988ec7-50de-411f-be77-bd6dceda85f0 · outbound

This paper cites On the completeness of orientation rules for causal discovery in the presence of latent confounders and selection bias.

Differentiable Causal Discovery For Latent Hierarchical Causal Models On the completeness of orientation rules for causal discovery in the presence of latent confounders and selection bias

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:16:37.641405Z

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 8a884fe1-a4f4-4b2b-b44e-531dbb4a9588 · outbound

This paper cites D-vae: A variational autoencoder for directed acyclic graphs.

Differentiable Causal Discovery For Latent Hierarchical Causal Models D-vae: A variational autoencoder for directed acyclic graphs

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:16:37.629679Z

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 796ab5e2-f3c5-4704-ab96-ba3e8d4be880 · outbound

This paper cites Dags with no tears: Continuous optimization for structure learning.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Dags with no tears: Continuous optimization for structure learning

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-12T10:16:37.337313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f2e9f6e-348f-42b6-b03f-d366d26f0720 · outbound

This paper cites Learning sparse nonparametric dags.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Learning sparse nonparametric dags

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:16:37.611100Z

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 5b582930-eefb-48cf-9f2f-9fa57d3b09f7 · outbound

This paper cites On the identifiability of nonlinear ica: Sparsity and beyond.

Differentiable Causal Discovery For Latent Hierarchical Causal Models On the identifiability of nonlinear ica: Sparsity and beyond

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-12T10:16:37.344688Z

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Observation c38402d6-4410-4740-83be-24ce714ee74f · outbound

This paper cites write newline.

Differentiable Causal Discovery For Latent Hierarchical Causal Models write newline

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-12T10:16:37.348446Z

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Unavailable: canonical work link unavailable.

Observation c4e73a0b-622c-4717-ac86-94267484893c · outbound

This paper cites @esa (Ref.

Differentiable Causal Discovery For Latent Hierarchical Causal Models @esa (Ref

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-12T10:16:37.353027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 265af921-9ca1-4955-8679-b7a22531b072 · outbound

This paper cites an unresolved cited work.

Differentiable Causal Discovery For Latent Hierarchical Causal Models Unresolved cited work

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-12T10:16:37.357095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4997d5f7-a547-4158-9ccb-62042356c096 · outbound

This paper cites silva2006learning and kummerfeld2016causal utilize tetrad conditions---the rank of each 2 2 sub-covariance matrix---to discover latent variables.

Differentiable Causal Discovery For Latent Hierarchical Causal Models silva2006learning and kummerfeld2016causal utilize tetrad conditions---the rank of each 2 2 sub-covariance matrix---to discover latent variables

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:16:37.572131Z

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.

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