Workshop
Causal Representation Learning
Sara Magliacane 路 Atalanti Mastakouri 路 Yuki Asano 路 Claudia Shi 路 Cian Eastwood 路 S茅bastien Lachapelle 路 Bernhard Sch枚lkopf 路 Caroline Uhler
Room 243 - 245
Fri 15 Dec, 6:15 a.m. PST
Can we learn causal representations from raw data, e.g. images? This workshop connects research in causality and representation learning.
Chat is not available.
Timezone: America/Los_Angeles
Schedule
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Fri 6:15 a.m. - 6:20 a.m.
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Introductory remarks
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Talk
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SlidesLive Video |
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Fri 6:20 a.m. - 6:50 a.m.
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Invited talk by Gemma Moran (Rutgers) - Identifiable representation learning via sparse decoding
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Talk
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SlidesLive Video |
Gemma Moran 馃敆 |
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Fri 6:50 a.m. - 7:20 a.m.
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Invited talk by Xinwei Shen (ETH) - Extrapolation in Regression and Representation Learning
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Talk
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SlidesLive Video |
Xinwei Shen 馃敆 |
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Fri 7:20 a.m. - 7:35 a.m.
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Identifying Effects of Disease on Single-Cells with Domain-Invariant Generative Modeling
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Talk
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SlidesLive Video |
Abdul Moeed 馃敆 |
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Fri 7:35 a.m. - 7:50 a.m.
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Identifying Representations for Intervention Extrapolation
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Talk
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SlidesLive Video |
Sorawit Saengkyongam 馃敆 |
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Fri 7:50 a.m. - 8:05 a.m.
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The Linear Representation Hypothesis in Language Models
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Talk
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SlidesLive Video |
Kiho Park 馃敆 |
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Fri 8:05 a.m. - 8:30 a.m.
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Coffee break and Poster session setup
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Fri 8:30 a.m. - 10:00 a.m.
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Poster session
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Posters
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Fri 10:00 a.m. - 11:30 a.m.
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Lunch break (optionally cont. poster session)
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Fri 11:30 a.m. - 12:00 p.m.
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Invited talk by Chandler Squires (MIT) - Causal Imputation and Causal Disentanglement
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Talk
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SlidesLive Video |
Chandler Squires 馃敆 |
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Fri 12:00 p.m. - 12:30 p.m.
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Invited talk by Dhanya Sridhar (MILA) - Properties of Representations for Causal Inference
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Talk
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SlidesLive Video |
Dhanya Sridhar 馃敆 |
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Fri 12:30 p.m. - 12:45 p.m.
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Multi-View Causal Representation Learning with Partial Observability
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Talk
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SlidesLive Video |
Dingling Yao 馃敆 |
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Fri 12:45 p.m. - 1:00 p.m.
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Score-based Causal Representation Learning from Interventions: Nonparametric Identifiability
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Talk
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link
SlidesLive Video |
Burak Var谋c谋 馃敆 |
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Fri 1:00 p.m. - 1:30 p.m.
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Coffee break (optionally cont. poster session)
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Fri 1:30 p.m. - 2:00 p.m.
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Invited talk by Francesco Locatello (ISTA) - Identifiability lessons learned scaling up causal discovery and causal representation learning
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Talk
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SlidesLive Video |
Francesco Locatello 馃敆 |
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Fri 2:00 p.m. - 2:30 p.m.
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Invited talk by Julius von K眉gelgen (MPI T眉bingen) - Nonparametric Causal Representation Learning from Multiple Environments
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Talk
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SlidesLive Video |
Julius von K眉gelgen 馃敆 |
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Fri 2:30 p.m. - 3:20 p.m.
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Panel discussion
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Panel
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SlidesLive Video |
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Fri 3:20 p.m. - 3:30 p.m.
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Closing remarks
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Talk
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Learning Object Motion and Appearance Dynamics with Object-Centric Representations ( Poster ) > link | Yeon-Ji Song 路 Hyunseo Kim 路 Suhyung Choi 路 Jin-Hwa Kim 路 Byoung-Tak Zhang 馃敆 |
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Attention for Causal Relationship Discovery from Biological Neural Dynamics ( Poster ) > link | Ziyu Lu 路 Anika Tabassum 路 Shruti Kulkarni 路 Lu Mi 路 Nathan Kutz 路 Eric Shea-Brown 路 Seung-Hwan Lim 馃敆 |
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Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control ( Poster ) > link | Neehal Tumma 路 Mathias Lechner 路 Noel Loo 路 Ramin Hasani 路 Daniela Rus 馃敆 |
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What's your Use Case? A Taxonomy of Causal Evaluations of Post-hoc Interpretability ( Poster ) > link | David Reber 路 Victor Veitch 馃敆 |
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Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Data ( Poster ) > link | Yuqin Yang 路 Saber Salehkaleybar 路 Negar Kiyavash 馃敆 |
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Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms ( Poster ) > link | Aneesh Komanduri 路 Yongkai Wu 路 Feng Chen 路 Xintao Wu 馃敆 |
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Towards Characterizing Domain Counterfactuals for Invertible Latent Causal Models ( Poster ) > link | Sean Kulinski 路 Zeyu Zhou 路 Ruqi Bai 路 Murat Kocaoglu 路 David Inouye 馃敆 |
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SCADI: Self-supervised Causal Disentanglement in Latent Variable Models ( Poster ) > link | Heejeong Nam 馃敆 |
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Inverted-Attention Transformers can Learn Object Representations: Insights from Slot Attention ( Poster ) > link | Yi-Fu Wu 路 Klaus Greff 路 Gamaleldin Elsayed 路 Michael Mozer 路 Thomas Kipf 路 Sjoerd van Steenkiste 馃敆 |
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Triangular Monotonic Generative Models Can Perform Causal Discovery ( Poster ) > link | Quanhan (Johnny) Xi 路 Sebastian Gonzalez 路 Benjamin Bloem-Reddy 馃敆 |
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Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs ( Poster ) > link | Jacqueline Maasch 路 Weishen Pan 路 Shantanu Gupta 路 Volodymyr Kuleshov 路 Kyra Gan 路 Fei Wang 馃敆 |
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Towards representation learning for general weighting problems in causal inference ( Poster ) > link | Oscar Clivio 路 Avi Feller 路 Chris C Holmes 馃敆 |
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Exploiting Causal Representations in Reinforcement Learning: A Posterior Sampling Approach ( Poster ) > link | Mirco Mutti 路 Riccardo De Santi 路 Marcello Restelli 路 Alexander Marx 路 Giorgia Ramponi 馃敆 |
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Identifying Effects of Disease on Single-Cells with Domain-Invariant Generative Modeling ( Oral ) > link | Abdul Moeed 路 Martin Rohbeck 路 Pavlo Lutsik 路 Kai Ueltzhoeffer 路 Marc Jan Bonder 路 Oliver Stegle 馃敆 |
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Learning Endogenous Representation in Reinforcement Learning via Advantage Estimation ( Poster ) > link | Hsiao-Ru Pan 路 Bernhard Sch枚lkopf 馃敆 |
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Causal Regressions For Unstructured Data ( Poster ) > link | Amandeep Singh 路 Bolong Zheng 馃敆 |
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Expediting Reinforcement Learning by Incorporating Temporal Causal Information ( Poster ) > link | Jan Corazza 路 Daniel Neider 路 Zhe Xu 路 Hadi Partovi Aria 馃敆 |
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DISK: Domain Inference for Discovering Spurious Correlation with KL-Divergence ( Poster ) > link | Yujin Han 路 Difan Zou 馃敆 |
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A Sparsity Principle for Partially Observable Causal Representation Learning ( Poster ) > link | Danru Xu 路 Dingling Yao 路 S茅bastien Lachapelle 路 Perouz Taslakian 路 Julius von K眉gelgen 路 Francesco Locatello 路 Sara Magliacane 馃敆 |
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Mixup-Based Knowledge Distillation with Causal Intervention for Multi-Task Speech Classification ( Poster ) > link | Kwangje Baeg 路 Hyeopwoo Lee 路 Yeomin Yoon 路 Jongmo Kim 馃敆 |
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Hierarchical Causal Representation Learning ( Poster ) > link | Angelos Nalmpantis 路 Phillip Lippe 路 Sara Magliacane 馃敆 |
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The Linear Representation Hypothesis in Language Models ( Oral ) > link | Kiho Park 路 Yo Joong Choe 路 Victor Veitch 馃敆 |
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Debiasing Multimodal Models via Causal Information Minimization ( Poster ) > link | Vaidehi Patil 路 Adyasha Maharana 路 Mohit Bansal 馃敆 |
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Unfairness Detection within Power Systems through Transfer Counterfactual Learning ( Poster ) > link | Song Wei 路 Xiangrui Kong 路 Sarah Huestis-Mitchell 路 Yao Xie 路 Shixiang Zhu 路 Alinson Xavier 路 Feng Qiu 馃敆 |
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Choice Models and Permutation Invariance: Demand Estimation in Differentiated Products Markets ( Poster ) > link | Amandeep Singh 路 Ye Liu 路 Hema Yoganarasimhan 馃敆 |
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Independent Mechanism Analysis and the Manifold Hypothesis: Identifiability and Genericity ( Poster ) > link | Shubhangi Ghosh 路 Luigi Gresele 路 Julius von K眉gelgen 路 Michel Besserve 路 Bernhard Sch枚lkopf 馃敆 |
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Cells2Vec: Bridging the gap between experiments and simulations using causal representation learning ( Poster ) > link | Dhruva Rajwade 路 Atiyeh Ahmadi 路 Brian Ingalls 馃敆 |
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Score-based Causal Representation Learning from Interventions: Nonparametric Identifiability ( Oral ) > link | Burak Var谋c谋 路 Emre Acart眉rk 路 Karthikeyan Shanmugam 路 Ali Tajer 馃敆 |
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Multi-Domain Causal Representation Learning via Weak Distributional Invariances ( Poster ) > link | Kartik Ahuja 路 Amin Mansouri 路 Yixin Wang 馃敆 |
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Counterfactual Generative Models for Time-Varying Treatments ( Poster ) > link | Shenghao Wu 路 Wenbin Zhou 路 Minshuo Chen 路 Shixiang Zhu 馃敆 |
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Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations ( Poster ) > link | Cian Eastwood 路 Julius von K眉gelgen 路 Linus Ericsson 路 Diane Bouchacourt 路 Pascal Vincent 路 Mark Ibrahim 路 Bernhard Sch枚lkopf 馃敆 |
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Object-Centric Semantic Vector Quantization ( Poster ) > link | Yi-Fu Wu 路 Minseung Lee 路 Sungjin Ahn 馃敆 |
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Towards the Reusability and Compositionality of Causal Representations ( Poster ) > link | Davide Talon 路 Phillip Lippe 路 Stuart James 路 Alessio Del Bue 路 Sara Magliacane 馃敆 |
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Object-centric architectures enable efficient causal representation learning ( Poster ) > link | Amin Mansouri 路 Jason Hartford 路 Yan Zhang 路 Yoshua Bengio 馃敆 |
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Reward-Relevance-Filtered Linear Offline Reinforcement Learning ( Poster ) > link | Angela Zhou 馃敆 |
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Putting Causal Identification to the Test: Falsification using Multi-Environment Data ( Poster ) > link | Rickard Karlsson 路 葮tefan Creast膬 路 Jesse Krijthe 馃敆 |
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Multi-View Causal Representation Learning with Partial Observability ( Oral ) > link | Dingling Yao 路 Danru Xu 路 S茅bastien Lachapelle 路 Sara Magliacane 路 Perouz Taslakian 路 Georg Martius 路 Julius von K眉gelgen 路 Francesco Locatello 馃敆 |
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Invariance & Causal Representation Learning: Prospects and Limitations ( Poster ) > link | Simon Bing 路 Jonas Wahl 路 Urmi Ninad 路 Jakob Runge 馃敆 |
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Curvature and Causal Inference in Network Data ( Poster ) > link | Amirhossein Farzam 路 Allen Tannenbaum 路 Guillermo Sapiro 馃敆 |
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Causal Modeling with Stationary Diffusions ( Poster ) > link | Lars Lorch 路 Andreas Krause 路 Bernhard Sch枚lkopf 馃敆 |
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Learning to ignore: Single Source Domain Generalization via Oracle Regularization ( Poster ) > link | Dong Kyu Cho 路 Sanghack Lee 馃敆 |
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Instance-Dependent Partial Label Learning with Identifiable Causal Representations ( Poster ) > link | Yizhi Wang 路 Weijia Zhang 路 Min-Ling Zhang 馃敆 |
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Causal Markov Blanket Representations for Domain Generalization Prediction ( Poster ) > link | Naiyu Yin 路 Hanjing Wang 路 Tian Gao 路 Amit Dhurandhar 路 Qiang Ji 馃敆 |
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Identifying Representations for Intervention Extrapolation ( Oral ) > link | Sorawit Saengkyongam 路 Elan Rosenfeld 路 Pradeep Ravikumar 路 Niklas Pfister 路 Jonas Peters 馃敆 |
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Learning Causally-Aware Representations of Multi-Agent Interactions ( Poster ) > link | Yuejiang Liu 路 Ahmad Rahimi 路 Po-Chien Luan 路 Frano Raji膷 路 Alexandre Alahi 馃敆 |
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A Causal Ordering Prior for Unsupervised Representation Learning ( Poster ) > link | Avinash Kori 路 Pedro Sanchez 路 Konstantinos Vilouras 路 Ben Glocker 路 Sotirios Tsaftaris 馃敆 |
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Learning Macro Variables with Auto-encoders ( Poster ) > link | Dhanya Sridhar 路 Eric Elmoznino 路 Maitreyi Swaroop 馃敆 |