Michael Mozer

Publication Activity (10 Years)

Years Active: 1988-2024
Publications (10 Years): 31

Top Topics

Vector Quantization

Model Based Reinforcement Learning

Mathematical Problem Solving

Top Venues

Publications

Haonan Wang, James Zou, Michael Mozer, Anirudh Goyal, Alex Lamb, Linjun Zhang, Weijie J. Su, Zhun Deng, Michael Qizhe Xie, Hannah Brown, Kenji Kawaguchi
Can AI Be as Creative as Humans? CoRR (2024)
Vedant Shah, Dingli Yu, Kaifeng Lyu, Simon Park, Nan Rosemary Ke, Michael Mozer, Yoshua Bengio, Sanjeev Arora, Anirudh Goyal
AI-Assisted Generation of Difficult Math Questions. CoRR (2024)
Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy P. Lillicrap, Danilo J. Rezende, Yoshua Bengio, Michael Mozer, Sanjeev Arora
Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving. CoRR (2024)
Sumukh K. Aithal, Anirudh Goyal, Alex Lamb, Yoshua Bengio, Michael Mozer
Leveraging the Third Dimension in Contrastive Learning. CoRR (2023)
David Mayo, Tyler R. Scott, Mengye Ren, Gamaledin Elsayed, Katherine L. Hermann, Matt Jones, Michael Mozer
Multitask Learning Via Interleaving: A Neural Network Investigation. CogSci (2023)
Vedant Shah, Frederik Träuble, Ashish Malik, Hugo Larochelle, Michael Mozer, Sanjeev Arora, Yoshua Bengio, Anirudh Goyal
Unlearning via Sparse Representations. CoRR (2023)
Dianbo Liu, Alex Lamb, Xu Ji, Pascal Tikeng Notsawo Jr., Michael Mozer, Yoshua Bengio, Kenji Kawaguchi
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness. AAAI (2023)
Nan Rosemary Ke, Sara-Jane Dunn, Jörg Bornschein, Silvia Chiappa, Mélanie Rey, Jean-Baptiste Lespiau, Albin Cassirer, Jane X. Wang, Theophane Weber, David G. T. Barrett, Matthew M. Botvinick, Anirudh Goyal, Michael Mozer, Danilo J. Rezende
DiscoGen: Learning to Discover Gene Regulatory Networks. CoRR (2023)
Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Mozer, Nicolas Heess, Yoshua Bengio
Stateful active facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning. CoRR (2022)
Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Jörg Bornschein, Theophane Weber, Anirudh Goyal, Matthew M. Botvinick, Michael Mozer, Danilo Jimenez Rezende
Learning to Induce Causal Structure. CoRR (2022)
Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf
Discrete Key-Value Bottleneck. CoRR (2022)
Dianbo Liu, Alex Lamb, Xu Ji, Pascal Notsawo, Michael Mozer, Yoshua Bengio, Kenji Kawaguchi
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization. CoRR (2022)
Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Mozer, Nicolas Heess, Yoshua Bengio
Coordinating Policies Among Multiple Agents via an Intelligent Communication Channel. CoRR (2022)
Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio
Neural Production Systems. NeurIPS (2021)
Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo Jimenez Rezende, Michael Mozer, Yoshua Bengio, Chris Pal
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. NeurIPS Datasets and Benchmarks (2021)
Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo J. Rezende, Yoshua Bengio, Michael Mozer, Christopher J. Pal
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. CoRR (2021)
Anirudh Goyal, Aniket Didolkar, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio
Neural Production Systems. CoRR (2021)
Anirudh Goyal, Aniket Didolkar, Alex Lamb, Kartikeya Badola, Nan Rosemary Ke, Nasim Rahaman, Jonathan Binas, Charles Blundell, Michael Mozer, Yoshua Bengio
Coordination Among Neural Modules Through a Shared Global Workspace. CoRR (2021)
Alex Lamb, Anirudh Goyal, Agnieszka Slowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio
Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers. AISTATS (2021)
Zeqian Li, Michael Mozer, Jacob Whitehill
Compositional Embeddings for Multi-Label One-Shot Learning. WACV (2021)
Adam Winchell, Andrew S. Lan, Michael Mozer
Highlights as an Early Predictor of Student Comprehension and Interests. Cogn. Sci. 44 (11) (2020)
Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. ICML (2020)
Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Sergey Levine, Charles Blundell, Yoshua Bengio, Michael Mozer
Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems. CoRR (2020)
David Y. J. Kim, Adam Winchell, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk, Michael Mozer
Inferring Student Comprehension from Highlighting Patterns in Digital Textbooks: An Exploration in an Authentic Learning Platform. iTextbooks@AIED (2020)
Alex Lamb, Anirudh Goyal, Agnieszka Slowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio
Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers. CoRR (2020)
Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. CoRR (2020)
Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Yoshua Bengio, Michael Mozer
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations. ICML (2019)
Robert V. Lindsey, Aaron Daluiski, Sumit Chopra, Alexander Lachapelle, Michael Mozer, Serge Sicular, Douglas Hanel, Michael Gardner, Anurag Gupta, Robert Hotchkiss, Hollis Potter
Deep neural network improves fracture detection by clinicians. Proc. Natl. Acad. Sci. USA 115 (45) (2018)
Shirly Montero, Akshit Arora, Sean Kelly, Brent Milne, Michael Mozer
Does Deep Knowledge Tracing Model Interactions Among Skills? EDM (2018)
Adam Winchell, Michael Mozer, Andrew S. Lan, Phillip Grimaldi, Harold Pashler
Textbook annotations as an early predictor of student learning. EDM (2018)
Mohammad Khajah, Robert V. Lindsey, Michael Mozer
How Deep is Knowledge Tracing? EDM (2016)
Nicole Beckage, Michael Mozer, Eliana Colunga
Predicting a Child's Trajectory of Lexical Acquisition. CogSci (2015)
Mohammad Khajah, Yun Huang, José P. González-Brenes, Michael Mozer, Peter Brusilovsky
Integrating Knowledge Tracing and Item Response Theory: A Tale of Two Frameworks. UMAP Workshops (2014)
Mohammad Khajah, Rowan Wing, Robert V. Lindsey, Michael Mozer
Integrating latent-factor and knowledge-tracing models to predict individual differences in learning. EDM (2014)
Robert V. Lindsey, Michael Mozer, William J. Huggins, Harold Pashler
Optimizing Instructional Policies. NIPS (2013)
Mohammad Khajah, Robert V. Lindsey, Michael Mozer
Maximizing Students' Retention Via Spaced Review: Practical Guidance From Computational Models Of Memory. CogSci (2013)
Benjamin Link, Brittany Ann Kos, Tor D. Wager, Michael Mozer
Past Experience Influences Judgment of Pain: Prediction of Sequential Dependencies. CogSci (2011)
Michael Mozer, Harold Pashler, Matthew H. Wilder, Robert V. Lindsey, Matt Jones, Michael Jones
Improving Human Judgments by Decontaminating Sequential Dependencies. NIPS (2010)
Matthew H. Wilder, Matt Jones, Michael Mozer
Sequential effects reflect parallel learning of multiple environmental regularities. NIPS (2009)
Michael Mozer, Harold Pashler, Nicholas Cepeda, Robert V. Lindsey, Ed Vul
Predicting the Optimal Spacing of Study: A Multiscale Context Model of Memory. NIPS (2009)
Michael Mozer, David Baldwin
Experience-Guided Search: A Theory of Attentional Control. NIPS (2007)
Michael Mozer, Michael Shettel, Shaun Vecera
Top-Down Control of Visual Attention: A Rational Account. NIPS (2005)
Michael Mozer
How Practice Makes Perfect. ICCM (2004)
Lian Yan, Robert H. Dodier, Michael Mozer, Richard H. Wolniewicz
Optimizing Classifier Performance via an Approximation to the Wilcoxon-Mann-Whitney Statistic. ICML (2003)
Sepp Hochreiter, Michael Mozer, Klaus Obermayer
Coulomb Classifiers: Generalizing Support Vector Machines via an Analogy to Electrostatic Systems. NIPS (2002)
Sepp Hochreiter, Michael Mozer
A Discrete Probabilistic Memory Model for Discovering Dependencies in Time. ICANN (2001)
Richard S. Zemel, Michael Mozer
Localist Attractor Networks. Neural Comput. 13 (5) (2001)
Sepp Hochreiter, Michael Mozer
Beyond Maximum Likelihood and Density Estimation: A Sample-Based Criterion for Unsupervised Learning of Complex Models. NIPS (2000)
David B. Grimes, Michael Mozer
The Interplay of Symbolic and Subsymbolic Processes in Anagram Problem Solving. NIPS (2000)
Jay A. Alexander, Michael Mozer
Template-based procedures for neural network interpretation. Neural Networks 12 (3) (1999)
Richard S. Zemel, Michael Mozer
A Generative Model for Attractor Dynamics. NIPS (1999)
Michael Mozer, Richard H. Wolniewicz, David B. Grimes, Eric Johnson, Howard Kaushansky
Churn Reduction in the Wireless Industry. NIPS (1999)
Soo-Young Lee, Michael Mozer
Robust Recognition of Noisy and Superimposed Patterns via Selective Attention. NIPS (1999)
Sreerupa Das, Michael Mozer
Dynamic On-line Clustering and State Extraction: An Approach to Symbolic Learning. Neural Networks 11 (1) (1998)
Michael Mozer
A Principle for Unsupervised Hierarchical Decomposition of Visual Scenes. NIPS (1998)
Michael Mozer, Debra Miller
Parsing the Stream of Time: The Value of Event-Based Segmentation in a Complex Real-World Control Problem. Summer School on Neural Networks (1997)
Michael Mozer, Mark Sitton, Martha J. Farah
A Superadditive-Impairment Theory of Optic Aphasia. NIPS (1997)
Brad Calder, Dirk Grunwald, Michael P. Jones, Donald C. Lindsay, James H. Martin, Michael Mozer, Benjamin G. Zorn
Evidence-Based Static Branch Prediction Using Machine Learning. ACM Trans. Program. Lang. Syst. 19 (1) (1997)
Michael Mozer, Lucky Vidmar, Robert H. Dodier
The Neurothermostat: Predictive Optimal Control of Residential Heating Systems. NIPS (1996)
Richard S. Zemel, Christopher K. I. Williams, Michael Mozer
Lending direction to neural networks. Neural Networks 8 (4) (1995)
Brad Calder, Dirk Grunwald, Donald C. Lindsay, James H. Martin, Michael Mozer, Benjamin G. Zorn
Corpus-Based Static Branch Prediction. PLDI (1995)
Donald W. Mathis, Michael Mozer
On the Computational Utility of Consciousness. NIPS (1994)
Jay A. Alexander, Michael Mozer
Template-Based Algorithms for Connectionist Rule Extraction. NIPS (1994)
Sreerupa Das, Michael Mozer
A Unified Gradient-Descent/Clustering Architecture for Finite State Machine Induction. NIPS (1993)
Clayton McMillan, Michael Mozer, Paul Smolensky
Dynamic Conflict Resolution in a Connectionist Rule-Based System. IJCAI (1993)
Richard S. Zemel, Christopher K. I. Williams, Michael Mozer
Directional-Unit Boltzmann Machines. NIPS (1992)
Michael Mozer, Sreerupa Das
A Connectionist Symbol Manipulator that Discovers the Structure of Context-Free Languages. NIPS (1992)
Brian V. Bonnlander, Michael Mozer
Metamorphosis Networks: An Alternative to Constructive Models. NIPS (1992)
Michael Mozer, Richard S. Zemel, Marlene Behrmann
Learning to Segment Images Using Dynamic Feature Binding. NIPS (1991)
Clayton McMillan, Michael Mozer, Paul Smolensky
Rule Induction through Integrated Symbolic and Subsymbolic Processing. NIPS (1991)
Michael Mozer
Neural network music composition and the induction of multiscale temporal structure. Wissensbasierte Systeme (1991)
Michael Mozer
Induction of Multiscale Temporal Structure. NIPS (1991)
Michael Mozer, Jonathan Bachrach
SLUG: A Connectionist Architecture for Inferring the Structure of Finite-State Environments. Mach. Learn. 7 (1991)
Michael Mozer, Todd Soukup
Connectionist Music Composition Based on Melodic and Stylistic Constraints. NIPS (1990)
Michael Mozer
Discovering Discrete Distributed Representations. NIPS (1990)
Richard S. Zemel, Michael Mozer, Geoffrey E. Hinton
TRAFFIC: Recognizing Objects Using Hierarchical Reference Frame Transformations. NIPS (1989)
Michael Mozer, Jonathan Bachrach
Discovering the Structure of a Reactive Environment by Exploration. NIPS (1989)
Michael Mozer, Paul Smolensky
Skeletonization: A Technique for Trimming the Fat from a Network via Relevance Assessment. NIPS (1988)