Workshop on the Elements of Reasoning:
Objects, Structure, and Causality (OSC)
April 29, 2022, Virtual ICLR 2022 Workshop
Accepted papers (along with reviews) are hosted on the OSC Workshop OpenReview page.
All accepted papers will be presented as posters spread across two sessions (session assigment is indicated below), hosted on GatherTown. Orals will be live-streamed on the day of the workshop.
| Title | Authors | Session | |
|---|---|---|---|
| Object Representations as Fixed Points: Training Iterative Inference Algorithms with Implicit Differentiation (Oral) | Michael Chang, Thomas L. Griffiths, Sergey Levine | #2 | |
| Disentanglement and Generalization Under Correlation Shifts (Oral) | Christina M Funke, Paul Vicol, Kuan-Chieh Wang, Matthias Kuemmerer, Richard Zemel, Matthias Bethge | #2 | |
| Learning Fourier-Sparse Functions on DAGs (Oral) | Bastian Seifert, Chris Wendler, Markus Püschel | #1 | |
| On the Identifiability of Nonlinear ICA with Unconditional Priors (Oral) | Yujia Zheng, Ignavier Ng, Kun Zhang | #1 | |
| Action-Sufficient State Representation Learning for Control with Structural Constraints | Biwei Huang, Chaochao Lu, Liu Leqi, José Miguel Hernández-Lobato, Clark Glymour, Bernhard Schölkopf, Kun Zhang | #2 | |
| Object-centric Compositional Imagination for Visual Abstract Reasoning | Rim Assouel, Pau Rodriguez, Perouz Taslakian, David Vazquez, Yoshua Bengio | #2 | |
| Inductive Biases for Relational Tasks | Giancarlo Kerg, Sarthak Mittal, David Rolnick, Yoshua Bengio, Blake Aaron Richards, Guillaume Lajoie | #2 | |
| A Causal Viewpoint on Motor-Imagery Brainwave Decoding | Konstantinos Barmpas, Yannis Panagakis, Dimitrios Adamos, Nikolaos Laskaris, Stefanos Zafeiriou | #2 | |
| Causal Policy Ranking | Daniel McNamee, Hana Chockler | #1 | |
| CITRIS: Causal Identifiability from Temporal Intervened Sequences | Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M Asano, Taco Cohen, Efstratios Gavves | #1 | |
| Learning Articulated Rigid Body Dynamics Simulations From Video | Eric Heiden, Ziang Liu, Vibhav Vineet, Erwin Coumans, Gaurav Sukhatme | #1 | |
| Binding Actions to Objects in World Models | Ondrej Biza, Robert Platt, Jan-Willem van de Meent, Lawson L.S. Wong, Thomas Kipf | #2 | |
| Learning to reason about and to act on physical cascading events | Yuval Atzmon, Eli Meirom, Shie Mannor, Gal Chechik | #2 | |
| Improving Generalization with Approximate Factored Value Functions | Shagun Sodhani, Sergey Levine, Amy Zhang | #2 | |
| DAG Learning on the Permutahedron | Valentina Zantedeschi, Jean Kaddour, Luca Franceschi, Matt Kusner, Vlad Niculae | #1 | |
| Continuous Relaxation For The Multivariate Noncentral Hypergeometric Distribution | Thomas M. Sutter, Laura Manduchi, Alain Ryser, Julia E Vogt | #1 | |
| INFERNO: Inferring Object-Centric 3D Scene Representations without Supervision | Lluis Castrejon, Nicolas Ballas, Aaron Courville | #2 | |
| Coherence Evaluation of Visual Concepts With Objects and Language | Tobias Leemann, Yao Rong, Stefan Kraft, Enkelejda Kasneci, Gjergji Kasneci | #1 | |
| Towards Self-Supervised Learning of Global and Object-Centric Representations | Federico Baldassarre, Hossein Azizpour | #1 | |
| Compositional Multi-object Reinforcement Learning with Linear Relation Networks | Davide Mambelli, Frederik Träuble, Stefan Bauer, Bernhard Schölkopf, Francesco Locatello | #1 | |
| Object-Centric Learning as Nested Optimization | Michael Chang, Sergey Levine, Thomas L. Griffiths | #2 | |
| Factorized World Models for Learning Causal Relationships | Artem Zholus, Yaroslav Ivchenkov, Aleksandr Panov | #1 | |
| Recognizing Actions using Object States | Nirat Saini, Bo He, Gaurav Shrivastava, Sai Saketh Rambhatla, Abhinav Shrivastava | #2 | |
| Align-Deform-Subtract: An interventional framework for explaining object differences | Cian Eastwood, Li Nanbo, Chris Williams | #1 | |
| LogicInference: A new Datasaet for Teaching Logical Inference to seq2seq Models | Santiago Ontanon, Joshua Ainslie, Vaclav Cvicek, Zachary Fisher | #2 | |
| Learning Two-Step Hybrid Policy for Graph-Based Interpretable Reinforcement Learning | Tongzhou Mu, Kaixiang Lin, Feiyang Niu, Govind Thattai | #2 | |
| Weakly supervised causal representation learning | Johann Brehmer, Pim De Haan, Phillip Lippe, Taco Cohen | #1 | |
| Discovering Generalizable Spatial Goal Representations via Graph-based Active Reward Learning | Aviv Netanyahu, Tianmin Shu, Joshua B. Tenenbaum, Pulkit Agrawal | #2 | |
| ReMixer: Object-aware Mixing Layer for Vision Transformers and Mixers | Hyunwoo Kang, Sangwoo Mo, Jinwoo Shin | #2 | |
| Invariant Causal Representation Learning for Generalization in Imitation and Reinforcement Learning | Chaochao Lu, José Miguel Hernández-Lobato, Bernhard Schölkopf | #1 | |
| Finding Structure and Causality in Linear Programs | Matej Zečević, Florian Peter Busch, Devendra Singh Dhami, Kristian Kersting | #2 |