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Workshop

Causal Representation Learning

Sara Magliacane · Atalanti Mastakouri · Yuki Asano · Claudia Shi · Cian Eastwood · Sébastien Lachapelle · Bernhard Schölkopf · Caroline Uhler
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Abstract

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Schedule

Timezone: America/Los_Angeles
Learning Object Motion and Appearance Dynamics with Object-Centric Representations Poster
Yeon-Ji Song · Hyunseo Kim · Suhyung Choi · Jin-Hwa Kim · Byoung-Tak Zhang
Attention for Causal Relationship Discovery from Biological Neural Dynamics Poster
Ziyu Lu · Anika Tabassum · Shruti Kulkarni · Lu Mi · Nathan Kutz · Eric Shea-Brown · Seung-Hwan Lim
Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control Poster
Neehal Tumma · Mathias Lechner · Noel Loo · Ramin Hasani · Daniela Rus
Towards Characterizing Domain Counterfactuals for Invertible Latent Causal Models Poster
Sean Kulinski · Zeyu Zhou · Ruqi Bai · Murat Kocaoglu · David Inouye
Inverted-Attention Transformers can Learn Object Representations: Insights from Slot Attention Poster
Yi-Fu Wu · Klaus Greff · Gamaleldin Elsayed · Michael Mozer · Thomas Kipf · Sjoerd van Steenkiste
Triangular Monotonic Generative Models Can Perform Causal Discovery Poster
Quanhan (Johnny) Xi · Sebastian Gonzalez · Benjamin Bloem-Reddy
Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs Poster
Jacqueline Maasch · Weishen Pan · Shantanu Gupta · Volodymyr Kuleshov · Kyra Gan · Fei Wang
Exploiting Causal Representations in Reinforcement Learning: A Posterior Sampling Approach Poster
Mirco Mutti · Riccardo De Santi · Marcello Restelli · Alexander Marx · Giorgia Ramponi
Identifying Effects of Disease on Single-Cells with Domain-Invariant Generative Modeling Oral
Abdul Moeed · Martin Rohbeck · Pavlo Lutsik · Kai Ueltzhoeffer · Marc Jan Bonder · Oliver Stegle
Causal Regressions For Unstructured Data Poster
Amandeep Singh · Bolong Zheng
Expediting Reinforcement Learning by Incorporating Temporal Causal Information Poster
Jan Corazza · Daniel Neider · Zhe Xu · Hadi Partovi Aria
A Sparsity Principle for Partially Observable Causal Representation Learning Poster
Danru Xu · Dingling Yao · Sébastien Lachapelle · Perouz Taslakian · Julius von Kügelgen · Francesco Locatello · Sara Magliacane
Hierarchical Causal Representation Learning Poster
Angelos Nalmpantis · Phillip Lippe · Sara Magliacane
The Linear Representation Hypothesis in Language Models Oral
Kiho Park · Yo Joong Choe · Victor Veitch
Debiasing Multimodal Models via Causal Information Minimization Poster
Vaidehi Patil · Adyasha Maharana · Mohit Bansal
Unfairness Detection within Power Systems through Transfer Counterfactual Learning Poster
Song Wei · Xiangrui Kong · Sarah Huestis-Mitchell · Yao Xie · Shixiang Zhu · Alinson Xavier · Feng Qiu
Independent Mechanism Analysis and the Manifold Hypothesis: Identifiability and Genericity Poster
Shubhangi Ghosh · Luigi Gresele · Julius von Kügelgen · Michel Besserve · Bernhard Schölkopf
Score-based Causal Representation Learning from Interventions: Nonparametric Identifiability Oral
Burak Varıcı · Emre Acartürk · Karthikeyan Shanmugam · Ali Tajer
Counterfactual Generative Models for Time-Varying Treatments Poster
Shenghao Wu · Wenbin Zhou · Minshuo Chen · Shixiang Zhu
Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations Poster
Cian Eastwood · Julius von Kügelgen · Linus Ericsson · Diane Bouchacourt · Pascal Vincent · Mark Ibrahim · Bernhard Schölkopf
Object-Centric Semantic Vector Quantization Poster
Yi-Fu Wu · Minseung Lee · Sungjin Ahn
Towards the Reusability and Compositionality of Causal Representations Poster
Davide Talon · Phillip Lippe · Stuart James · Alessio Del Bue · Sara Magliacane
Object-centric architectures enable efficient causal representation learning Poster
Amin Mansouri · Jason Hartford · Yan Zhang · Yoshua Bengio
Multi-View Causal Representation Learning with Partial Observability Oral
Dingling Yao · Danru Xu · Sébastien Lachapelle · Sara Magliacane · Perouz Taslakian · Georg Martius · Julius von Kügelgen · Francesco Locatello
Invariance & Causal Representation Learning: Prospects and Limitations Poster
Simon Bing · Jonas Wahl · Urmi Ninad · Jakob Runge
Curvature and Causal Inference in Network Data Poster
Amirhossein Farzam · Allen Tannenbaum · Guillermo Sapiro
Causal Modeling with Stationary Diffusions Poster
Lars Lorch · Andreas Krause · Bernhard Schölkopf
Causal Markov Blanket Representations for Domain Generalization Prediction Poster
Naiyu Yin · Hanjing Wang · Tian Gao · Amit Dhurandhar · Qiang Ji
Identifying Representations for Intervention Extrapolation Oral
Sorawit Saengkyongam · Elan Rosenfeld · Pradeep Ravikumar · Niklas Pfister · Jonas Peters
Learning Causally-Aware Representations of Multi-Agent Interactions Poster
Yuejiang Liu · Ahmad Rahimi · Po-Chien Luan · Frano Rajič · Alexandre Alahi
A Causal Ordering Prior for Unsupervised Representation Learning Poster
Avinash Kori · Pedro Sanchez · Konstantinos Vilouras · Ben Glocker · Sotirios Tsaftaris
Learning Macro Variables with Auto-encoders Poster
Dhanya Sridhar · Eric Elmoznino · Maitreyi Swaroop