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