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CITRIS: Causal Identifiability from Temporal Intervened Sequences

International Conference on Machine Learning (ICML), 2022

7 February 2022

Papers citing "CITRIS: Causal Identifiability from Temporal Intervened Sequences"

46 / 46 papers shown

Title
Debiasing Reward Models by Representation Learning with Guarantees Ignavier Ng Patrick Blobaum Siddharth Bhandari Kun Zhang Shiva Prasad Kasiviswanathan 120 0 0 27 Oct 2025
Online Time Series Forecasting with Theoretical Guarantees Zijian Li Changze Zhou Minghao Fu Sanjay Manjunath Fan Feng Guangyi Chen Yingyao Hu Ruichu Cai Kun Zhang AI4TS OOD 112 0 0 21 Oct 2025
Provable Affine Identifiability of Nonlinear CCA under Latent Distributional Priors Zhiwei Han Stefan Matthes Hao Shen CML 109 0 0 06 Oct 2025
From Pixels to Factors: Learning Independently Controllable State Variables for Reinforcement Learning Rafael Rodríguez-Sánchez Cameron Allen George Konidaris OffRL 113 2 0 02 Oct 2025
Causal representation learning from network data Jifan Zhang Michelle M. Li Elena Zheleva OOD CML 70 0 0 02 Sep 2025
Structured Kernel Regression VAE: A Computationally Efficient Surrogate for GP-VAEs in ICA Yuan-Hao Wei Fu-Hao Deng Lin-Yong Cui Yan-Jie Sun CML 122 0 0 13 Aug 2025
Learning Robust Intervention Representations with Delta Embeddings Panagiotis Alimisis Christos Diou OOD CML 124 0 0 06 Aug 2025
Half-AVAE: Adversarial-Enhanced Factorized and Structured Encoder-Free VAE for Underdetermined Independent Component Analysis Yuan-Hao Wei Yan-Jie Sun 161 1 0 08 Jun 2025
When Does Closeness in Distribution Imply Representational Similarity? An Identifiability Perspective Beatrix M. G. Nielsen Emanuele Marconato Andrea Dittadi Luigi Gresele 199 2 0 04 Jun 2025
Incorporating Hierarchical Semantics in Sparse Autoencoder Architectures Mark Muchane Sean Richardson Kiho Park Victor Veitch 188 2 0 01 Jun 2025
The Third Pillar of Causal Analysis? A Measurement Perspective on Causal Representations Dingling Yao Shimeng Huang Riccardo Cadei Kun Zhang Francesco Locatello CML 386 1 0 23 May 2025
Learning Local Causal World Models with State Space Models and Attention Francesco Petri Luigi Asprino Aldo Gangemi CML 213 1 0 04 May 2025
Sanity Checking Causal Representation Learning on a Simple Real-World System Juan L. Gamella Simon Bing Jakob Runge CML 415 2 0 27 Feb 2025
Disentangling Long-Short Term State Under Unknown Interventions for Online Time Series ForecastingAAAI Conference on Artificial Intelligence (AAAI), 2025 Ruichu Cai Haiqin Huang Zhifang Jiang Zijian Li Changze Zhou Yuequn Liu Yuming Liu Zijian Li AI4TS CML 277 3 0 18 Feb 2025
Sample-efficient Learning of Concepts with Theoretical Guarantees: from Data to Concepts without Interventions H. Fokkema T. Erven Sara Magliacane 422 3 0 10 Feb 2025
What is causal about causal models and representations? Frederik Hytting Jørgensen Luigi Gresele S. Weichwald CML 523 3 0 31 Jan 2025
All or None: Identifiable Linear Properties of Next-token Predictors in Language ModelingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024 Emanuele Marconato Sébastien Lachapelle Sebastian Weichwald Luigi Gresele 316 6 0 30 Oct 2024
A Complexity-Based Theory of Compositionality Eric Elmoznino Thomas Jiralerspong Yoshua Bengio Guillaume Lajoie CoGe 634 17 0 18 Oct 2024
Self-supervised contrastive learning performs non-linear system identificationInternational Conference on Learning Representations (ICLR), 2024 Rodrigo González Laiz Tobias Schmidt Steffen Schneider SSL 243 3 0 18 Oct 2024
Causal Temporal Representation Learning with Nonstationary Sparse TransitionNeural Information Processing Systems (NeurIPS), 2024 Xiangchen Song Zijian Li Guangyi Chen Yujia Zheng Yewen Fan Xinshuai Dong Kun Zhang CML 182 7 0 05 Sep 2024
On the Identification of Temporally Causal Representation with Instantaneous Dependence Zijian Li Yifan Shen Kaitao Zheng Ruichu Cai Xiangchen Song Biwei Huang Zhengmao Zhu Guan-Hong Chen CML 498 11 0 24 May 2024
Marrying Causal Representation Learning with Dynamical Systems for Science Dingling Yao Caroline Muller Francesco Locatello CML AI4CE 371 18 0 22 May 2024
Identifiable Latent Neural Causal Models Yuhang Liu Zhen Zhang Dong Gong Biwei Huang Erdun Gao Anton Van Den Hengel Kun Zhang Javen Qinfeng Shi CML OOD 283 9 0 23 Mar 2024
Double Machine Learning Based Structure Identification from Temporal Data Emmanouil Angelis Francesco Quinzan Ashkan Soleymani Patrick Jaillet Stefan Bauer OOD CML 381 2 0 10 Nov 2023
Object-centric architectures enable efficient causal representation learningInternational Conference on Learning Representations (ICLR), 2023 Amin Mansouri Jason S. Hartford Yan Zhang Yoshua Bengio CML OCL OOD 242 24 0 29 Oct 2023
Temporally Disentangled Representation Learning under Unknown NonstationarityNeural Information Processing Systems (NeurIPS), 2023 Xiangchen Song Weiran Yao Yewen Fan Xinshuai Dong Guan-Hong Chen Juan Carlos Niebles Eric P. Xing Kun Zhang CML OOD 274 19 0 28 Oct 2023
Identifiable Latent Polynomial Causal Models Through the Lens of ChangeInternational Conference on Learning Representations (ICLR), 2023 Yuhang Liu Zhen Zhang Dong Gong Biwei Huang Erdun Gao Anton Van Den Hengel Kun Zhang Javen Qinfeng Shi 199 18 0 24 Oct 2023
From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling Aneesh Komanduri Xintao Wu Yongkai Wu Feng Chen CML OOD 436 22 0 17 Oct 2023
On the Identifiability of Quantized FactorsCLEaR (CLEaR), 2023 Vitória Barin Pacela Kartik Ahuja Damien Scieur Pascal Vincent OOD CML 242 3 0 28 Jun 2023
BISCUIT: Causal Representation Learning from Binary InteractionsConference on Uncertainty in Artificial Intelligence (UAI), 2023 Phillip Lippe Sara Magliacane Sindy Löwe Yuki M. Asano Taco S. Cohen E. Gavves CML 191 34 0 16 Jun 2023
Robustness and Generalization Performance of Deep Learning Models on Cyber-Physical Systems: A Comparative Study Alexander Windmann Henrik S. Steude Oliver Niggemann OOD AI4TS AAML 111 4 0 13 Jun 2023
Learning World Models with Identifiable FactorizationNeural Information Processing Systems (NeurIPS), 2023 Yu-Ren Liu Erdun Gao Zhengmao Zhu Hong Tian Biwei Huang Yang Yu Kun Zhang CML OffRL 256 17 0 11 Jun 2023
Learning nonparametric latent causal graphs with unknown interventionsNeural Information Processing Systems (NeurIPS), 2023 Yibo Jiang Bryon Aragam CML 250 28 0 05 Jun 2023
Nonparametric Identifiability of Causal Representations from Unknown InterventionsNeural Information Processing Systems (NeurIPS), 2023 Julius von Kügelgen M. Besserve Wendong Liang Luigi Gresele Armin Kekić Elias Bareinboim David M. Blei Bernhard Schölkopf CML 455 80 0 01 Jun 2023
Enhancing Causal Discovery from Robot Sensor Data in Dynamic ScenariosCLEaR (CLEaR), 2023 Luca Castri Sariah Mghames Marc Hanheide Nicola Bellotto CML 179 18 0 20 Feb 2023
Causal Triplet: An Open Challenge for Intervention-centric Causal Representation LearningCLEaR (CLEaR), 2023 Yuejiang Liu Alexandre Alahi Chris Russell Max Horn Dominik Zietlow Bernhard Schölkopf Francesco Locatello CML 219 27 0 12 Jan 2023
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 275 17 0 07 Nov 2022
Temporally Disentangled Representation LearningNeural Information Processing Systems (NeurIPS), 2022 Weiran Yao Guangyi Chen Kun Zhang CML BDL OOD 205 64 0 24 Oct 2022
Learning Latent Structural Causal Models Jithendaraa Subramanian Yashas Annadani Ivaxi Sheth Nan Rosemary Ke T. Deleu Stefan Bauer Derek Nowrouzezahrai Samira Ebrahimi Kahou CML 192 7 0 24 Oct 2022
Interventional Causal Representation LearningInternational Conference on Machine Learning (ICML), 2022 Kartik Ahuja Divyat Mahajan Yixin Wang Yoshua Bengio CML 380 114 0 24 Sep 2022
Partial Disentanglement via Mechanism Sparsity Sébastien Lachapelle Damien Scieur 135 29 0 15 Jul 2022
Towards a Grounded Theory of Causation for Embodied AI Taco S. Cohen CML 128 9 0 28 Jun 2022
Variational Causal Dynamics: Discovering Modular World Models from Interventions Anson Lei Bernhard Schölkopf Ingmar Posner CML 184 12 0 22 Jun 2022
Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift HypothesisNeural Information Processing Systems (NeurIPS), 2022 Ronan Perry Julius von Kügelgen Bernhard Schölkopf 329 58 0 04 Jun 2022
Weakly Supervised Representation Learning with Sparse PerturbationsNeural Information Processing Systems (NeurIPS), 2022 Kartik Ahuja Jason S. Hartford Yoshua Bengio SSL 235 70 0 02 Jun 2022
Weakly supervised causal representation learningNeural Information Processing Systems (NeurIPS), 2022 Johann Brehmer P. D. Haan Phillip Lippe Taco S. Cohen OOD CML 321 147 0 30 Mar 2022