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Michael C. Mozer
Michael Curtis Mozer – Michael Mozer
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- affiliation: University of Colorado, USA
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2020 – today
- 2024
- [c99]Matt Jones, Tyler R. Scott, Michael C. Mozer:
Human-like Learning in Temporally Structured Environments. AAAI Spring Symposia 2024: 553 - [c98]Katherine L. Hermann, Hossein Mobahi, Thomas Fel, Michael Curtis Mozer:
On the Foundations of Shortcut Learning. ICLR 2024 - [c97]Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy P. Lillicrap, Danilo Jimenez Rezende, Yoshua Bengio, Michael C. Mozer, Sanjeev Arora:
Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving. NeurIPS 2024 - [c96]Anand Gopalakrishnan, Aleksandar Stanic, Jürgen Schmidhuber, Michael C. Mozer:
Recurrent Complex-Weighted Autoencoders for Unsupervised Object Discovery. NeurIPS 2024 - [c95]Yanlai Yang, Matt Jones, Michael C. Mozer, Mengye Ren:
Reawakening knowledge: Anticipatory recovery from catastrophic interference via structured training. NeurIPS 2024 - [i57]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 abs/2401.01623 (2024) - [i56]Yanlai Yang, Matt Jones, Michael C. Mozer, Mengye Ren:
Reawakening knowledge: Anticipatory recovery from catastrophic interference via structured training. CoRR abs/2403.09613 (2024) - [i55]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 abs/2405.12205 (2024) - [i54]Anand Gopalakrishnan, Aleksandar Stanic, Jürgen Schmidhuber, Michael Curtis Mozer:
Recurrent Complex-Weighted Autoencoders for Unsupervised Object Discovery. CoRR abs/2405.17283 (2024) - [i53]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 abs/2407.21009 (2024) - [i52]Aniket Didolkar, Andrii Zadaianchuk, Anirudh Goyal, Michael C. Mozer, Yoshua Bengio, Georg Martius, Maximilian Seitzer:
Zero-Shot Object-Centric Representation Learning. CoRR abs/2408.09162 (2024) - [i51]Lukas Muttenthaler, Klaus Greff, Frieda Born, Bernhard Spitzer, Simon Kornblith, Michael C. Mozer, Klaus-Robert Müller, Thomas Unterthiner, Andrew K. Lampinen:
Aligning Machine and Human Visual Representations across Abstraction Levels. CoRR abs/2409.06509 (2024) - [i50]Michael A. Lepori, Michael Mozer, Asma Ghandeharioun:
Racing Thoughts: Explaining Large Language Model Contextualization Errors. CoRR abs/2410.02102 (2024) - [i49]Rushi Shah, Mingyuan Yan, Michael Curtis Mozer, Dianbo Liu:
Improving Discrete Optimisation Via Decoupled Straight-Through Gumbel-Softmax. CoRR abs/2410.13331 (2024) - [i48]Nan Rosemary Ke, Danny P. Sawyer, Hubert Soyer, Martin Engelcke, David P. Reichert, Drew A. Hudson, John Reid, Alexander Lerchner, Danilo Jimenez Rezende, Timothy P. Lillicrap, Michael Mozer, Jane X. Wang:
Can foundation models actively gather information in interactive environments to test hypotheses? CoRR abs/2412.06438 (2024) - 2023
- [j27]Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Bernhard Schölkopf, Michael Curtis Mozer, Christopher Pal, Yoshua Bengio:
Neural Causal Structure Discovery from Interventions. Trans. Mach. Learn. Res. 2023 (2023) - [c94]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: 8825-8833 - [c93]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 - [c92]Matt Jones, Tyler R. Scott, Mengye Ren, Gamaleldin Fathy Elsayed, Katherine L. Hermann, David Mayo, Michael Curtis Mozer:
Learning in temporally structured environments. ICLR 2023 - [c91]Nan Rosemary Ke, Silvia Chiappa, Jane X. Wang, Jörg Bornschein, Anirudh Goyal, Mélanie Rey, Theophane Weber, Matthew M. Botvinick, Michael Curtis Mozer, Danilo Jimenez Rezende:
Learning to Induce Causal Structure. ICLR 2023 - [c90]Dianbo Liu, Vedant Shah, Oussama Boussif
, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Curtis Mozer, Nicolas Heess, Yoshua Bengio:
Stateful Active Facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning. ICLR 2023 - [c89]Pratyush Maini, Michael Curtis Mozer, Hanie Sedghi, Zachary Chase Lipton, J. Zico Kolter, Chiyuan Zhang:
Can Neural Network Memorization Be Localized? ICML 2023: 23536-23557 - [c88]Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Curtis Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf:
Discrete Key-Value Bottleneck. ICML 2023: 34431-34455 - [i47]Sumukh K. Aithal, Anirudh Goyal, Alex Lamb, Yoshua Bengio, Michael Mozer:
Leveraging the Third Dimension in Contrastive Learning. CoRR abs/2301.11790 (2023) - [i46]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 abs/2304.05823 (2023) - [i45]Ayush Chakravarthy, Trang Nguyen, Anirudh Goyal, Yoshua Bengio, Michael C. Mozer:
Spotlight Attention: Robust Object-Centric Learning With a Spatial Locality Prior. CoRR abs/2305.19550 (2023) - [i44]Pratyush Maini, Michael C. Mozer, Hanie Sedghi, Zachary C. Lipton, J. Zico Kolter, Chiyuan Zhang:
Can Neural Network Memorization Be Localized? CoRR abs/2307.09542 (2023) - [i43]Katherine L. Hermann, Hossein Mobahi, Thomas Fel, Michael C. Mozer:
On the Foundations of Shortcut Learning. CoRR abs/2310.16228 (2023) - [i42]Vedant Shah, Frederik Träuble, Ashish Malik, Hugo Larochelle, Michael Mozer, Sanjeev Arora, Yoshua Bengio, Anirudh Goyal:
Unlearning via Sparse Representations. CoRR abs/2311.15268 (2023) - 2022
- [c87]Rebecca Roelofs, Nicholas Cain, Jonathon Shlens, Michael C. Mozer:
Mitigating Bias in Calibration Error Estimation. AISTATS 2022: 4036-4054 - [c86]Anirudh Goyal, Aniket Rajiv Didolkar, Alex Lamb, Kartikeya Badola, Nan Rosemary Ke, Nasim Rahaman, Jonathan Binas, Charles Blundell, Michael Curtis Mozer, Yoshua Bengio:
Coordination Among Neural Modules Through a Shared Global Workspace. ICLR 2022 - [c85]Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael C. Mozer:
Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning. ICML 2022: 6009-6033 - [c84]Gamaleldin F. Elsayed, Aravindh Mahendran, Sjoerd van Steenkiste, Klaus Greff, Michael C. Mozer, Thomas Kipf:
SAVi++: Towards End-to-End Object-Centric Learning from Real-World Videos. NeurIPS 2022 - [i41]Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael C. Mozer:
Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning. CoRR abs/2201.03529 (2022) - [i40]Dianbo Liu, Alex Lamb, Xu Ji, Pascal Notsawo, Michael Mozer, Yoshua Bengio, Kenji Kawaguchi:
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization. CoRR abs/2202.01334 (2022) - [i39]Shruthi Sukumar, Adrian F. Ward
, Camden Elliott-Williams, Shabnam Hakimi, Michael C. Mozer:
Overcoming Temptation: Incentive Design For Intertemporal Choice. CoRR abs/2203.05782 (2022) - [i38]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 abs/2204.04875 (2022) - [i37]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 abs/2205.10607 (2022) - [i36]Gamaleldin F. Elsayed, Aravindh Mahendran, Sjoerd van Steenkiste, Klaus Greff, Michael C. Mozer, Thomas Kipf:
SAVi++: Towards End-to-End Object-Centric Learning from Real-World Videos. CoRR abs/2206.07764 (2022) - [i35]Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf:
Discrete Key-Value Bottleneck. CoRR abs/2207.11240 (2022) - [i34]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 abs/2210.03022 (2022) - [i33]Tyler R. Scott, Ting Liu, Michael C. Mozer, Andrew C. Gallagher:
An Empirical Study on Clustering Pretrained Embeddings: Is Deep Strictly Better? CoRR abs/2211.05183 (2022) - [i32]Amr Khalifa, Michael C. Mozer, Hanie Sedghi, Behnam Neyshabur, Ibrahim Alabdulmohsin:
Layer-Stack Temperature Scaling. CoRR abs/2211.10193 (2022) - 2021
- [j26]Brett D. Roads, Michael C. Mozer:
Predicting the Ease of Human Category Learning Using Radial Basis Function Networks. Neural Comput. 33(2): 376-397 (2021) - [c83]David Y. J. Kim, Tyler R. Scott, Debshila Basu Mallick, Michael C. Mozer:
Using Semantics of Textbook Highlights to Predict Student Comprehension and Knowledge Retention. iTextbooks@AIED 2021: 108-120 - [c82]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: 919-927 - [c81]Tyler R. Scott, Andrew C. Gallagher, Michael C. Mozer:
von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning. ICCV 2021: 10592-10602 - [c80]Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Charles Blundell, Sergey Levine, Yoshua Bengio, Michael Curtis Mozer:
Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments. ICLR 2021 - [c79]Mengye Ren, Michael Louis Iuzzolino, Michael Curtis Mozer, Richard S. Zemel:
Wandering within a world: Online contextualized few-shot learning. ICLR 2021 - [c78]Ziheng Jiang, Chiyuan Zhang, Kunal Talwar, Michael C. Mozer:
Characterizing Structural Regularities of Labeled Data in Overparameterized Models. ICML 2021: 5034-5044 - [c77]Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Michael C. Mozer:
Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers. ICML 2021: 10225-10235 - [c76]Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael C. Mozer, Yoshua Bengio:
Discrete-Valued Neural Communication. NeurIPS 2021: 2109-2121 - [c75]Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio:
Neural Production Systems. NeurIPS 2021: 25673-25687 - [c74]Michael L. Iuzzolino, Michael C. Mozer, Samy Bengio:
Improving Anytime Prediction with Parallel Cascaded Networks and a Temporal-Difference Loss. NeurIPS 2021: 27631-27644 - [c73]Archit Karandikar, Nicholas Cain, Dustin Tran, Balaji Lakshminarayanan, Jonathon Shlens, Michael C. Mozer, Becca Roelofs:
Soft Calibration Objectives for Neural Networks. NeurIPS 2021: 29768-29779 - [c72]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 - [c71]Zeqian Li, Michael Mozer, Jacob Whitehill:
Compositional Embeddings for Multi-Label One-Shot Learning. WACV 2021: 296-304 - [i31]Michael L. Iuzzolino, Michael C. Mozer, Samy Bengio:
Training cascaded networks for speeded decisions using a temporal-difference loss. CoRR abs/2102.09808 (2021) - [i30]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 abs/2103.01197 (2021) - [i29]Anirudh Goyal, Aniket Didolkar, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio:
Neural Production Systems. CoRR abs/2103.01937 (2021) - [i28]Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Michael C. Mozer:
Understanding invariance via feedforward inversion of discriminatively trained classifiers. CoRR abs/2103.07470 (2021) - [i27]Tyler R. Scott, Andrew C. Gallagher, Michael C. Mozer:
von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning. CoRR abs/2103.15718 (2021) - [i26]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 abs/2107.00848 (2021) - [i25]Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael Curtis Mozer, Yoshua Bengio:
Discrete-Valued Neural Communication. CoRR abs/2107.02367 (2021) - [i24]Archit Karandikar, Nicholas Cain, Dustin Tran, Balaji Lakshminarayanan, Jonathon Shlens, Michael C. Mozer, Becca Roelofs:
Soft Calibration Objectives for Neural Networks. CoRR abs/2108.00106 (2021) - [i23]Nino Scherrer, Olexa Bilaniuk, Yashas Annadani, Anirudh Goyal, Patrick Schwab, Bernhard Schölkopf, Michael C. Mozer, Yoshua Bengio, Stefan Bauer, Nan Rosemary Ke:
Learning Neural Causal Models with Active Interventions. CoRR abs/2109.02429 (2021) - [i22]Mengye Ren, Tyler R. Scott, Michael L. Iuzzolino, Michael C. Mozer, Richard S. Zemel:
Online Unsupervised Learning of Visual Representations and Categories. CoRR abs/2109.05675 (2021) - 2020
- [j25]Adam Winchell
, Andrew S. Lan
, Michael Mozer
:
Highlights as an Early Predictor of Student Comprehension and Interests. Cogn. Sci. 44(11) (2020) - [j24]Nicole M. Beckage
, Michael C. Mozer
, Eliana Colunga:
Quantifying the Role of Vocabulary Knowledge in Predicting Future Word Learning. IEEE Trans. Cogn. Dev. Syst. 12(2): 148-159 (2020) - [c70]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: 67-79 - [c69]Guy Davidson, Michael C. Mozer:
Sequential Mastery of Multiple Visual Tasks: Networks Naturally Learn to Learn and Forget to Forget. CVPR 2020: 9279-9290 - [c68]Chiyuan Zhang, Samy Bengio, Moritz Hardt, Michael C. Mozer, Yoram Singer:
Identity Crisis: Memorization and Generalization Under Extreme Overparameterization. ICLR 2020 - [c67]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: 6972-6986 - [i21]Ziheng Jiang, Chiyuan Zhang, Kunal Talwar, Michael C. Mozer:
Exploring the Memorization-Generalization Continuum in Deep Learning. CoRR abs/2002.03206 (2020) - [i20]Zeqian Li, Michael C. Mozer, Jacob Whitehill:
Compositional Embeddings for Multi-Label One-Shot Learning. CoRR abs/2002.04193 (2020) - [i19]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 abs/2006.16225 (2020) - [i18]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 abs/2006.16981 (2020) - [i17]Mengye Ren, Michael L. Iuzzolino, Michael C. Mozer, Richard S. Zemel:
Wandering Within a World: Online Contextualized Few-Shot Learning. CoRR abs/2007.04546 (2020) - [i16]Maria Attarian, Brett D. Roads, Michael C. Mozer:
Transforming Neural Network Visual Representations to Predict Human Judgments of Similarity. CoRR abs/2010.06512 (2020) - [i15]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 abs/2010.08012 (2020) - [i14]Rebecca Roelofs, Nicholas Cain, Jonathon Shlens, Michael C. Mozer:
Mitigating bias in calibration error estimation. CoRR abs/2012.08668 (2020)
2010 – 2019
- 2019
- [c66]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: 3622-3631 - [i13]Guy Davidson, Michael C. Mozer:
Sequential mastery of multiple tasks: Networks naturally learn to learn. CoRR abs/1905.10837 (2019) - [i12]Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Denis Kazakov, Yoshua Bengio, Michael C. Mozer:
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations. CoRR abs/1905.11382 (2019) - [i11]Michael L. Iuzzolino, Yoram Singer, Michael C. Mozer:
Convolutional Bipartite Attractor Networks. CoRR abs/1906.03504 (2019) - [i10]Tyler R. Scott, Karl Ridgeway, Michael C. Mozer:
Stochastic Prototype Embeddings. CoRR abs/1909.11702 (2019) - 2018
- [j23]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): 11591-11596 (2018) - [c65]Mohammad M. Khajah, Michael C. Mozer, Sean Kelly, Brent Milne:
Boosting Engagement with Educational Software Using Near Wins. AIED (2) 2018: 171-175 - [c64]Shirly Montero, Akshit Arora, Sean Kelly, Brent Milne, Michael Mozer:
Does Deep Knowledge Tracing Model Interactions Among Skills? EDM 2018 - [c63]Adam Winchell, Michael Mozer, Andrew S. Lan, Phillip Grimaldi, Harold Pashler:
Textbook annotations as an early predictor of student learning. EDM 2018 - [c62]Tyler R. Scott, Karl Ridgeway, Michael C. Mozer:
Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning. NeurIPS 2018: 76-85 - [c61]Karl Ridgeway, Michael C. Mozer:
Learning Deep Disentangled Embeddings With the F-Statistic Loss. NeurIPS 2018: 185-194 - [c60]Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Michael C. Mozer, Chris Pal, Yoshua Bengio:
Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding. NeurIPS 2018: 7651-7662 - [i9]Karl Ridgeway, Michael C. Mozer:
Learning Deep Disentangled Embeddings with the F-Statistic Loss. CoRR abs/1802.05312 (2018) - [i8]Michael C. Mozer, Denis Kazakov, Robert V. Lindsey:
State-Denoised Recurrent Neural Networks. CoRR abs/1805.08394 (2018) - [i7]Tyler R. Scott, Karl Ridgeway, Michael C. Mozer:
Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning. CoRR abs/1805.08402 (2018) - [i6]Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Michael C. Mozer, Chris Pal, Yoshua Bengio:
Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding. CoRR abs/1809.03702 (2018) - [i5]Karl Ridgeway, Michael C. Mozer:
Open-Ended Content-Style Recombination Via Leakage Filtering. CoRR abs/1810.00110 (2018) - 2017
- [j22]Karl Ridgeway, Michael C. Mozer, Anita R. Bowles:
Forgetting of Foreign-Language Skills: A Corpus-Based Analysis of Online Tutoring Software. Cogn. Sci. 41(4): 924-949 (2017) - [j21]Brett D. Roads, Michael C. Mozer:
Improving Human-Machine Cooperative Classification Via Cognitive Theories of Similarity. Cogn. Sci. 41(5): 1394-1411 (2017) - [j20]Ronald T. Kneusel, Michael C. Mozer:
Improving Human-Machine Cooperative Visual Search With Soft Highlighting. ACM Trans. Appl. Percept. 15(1): 3:1-3:21 (2017) - [c59]Jake Snell, Karl Ridgeway, Renjie Liao, Brett D. Roads, Michael C. Mozer, Richard S. Zemel:
Learning to generate images with perceptual similarity metrics. ICIP 2017: 4277-4281 - [i4]Michael C. Mozer, Denis Kazakov, Robert V. Lindsey:
Discrete Event, Continuous Time RNNs. CoRR abs/1710.04110 (2017) - 2016
- [c58]Mohammad Khajah, Brett D. Roads, Robert V. Lindsey, Yun-En Liu, Michael C. Mozer:
Designing Engaging Games Using Bayesian Optimization. CHI 2016: 5571-5582 - [c57]Mohammad Khajah, Robert V. Lindsey, Michael Mozer:
How Deep is Knowledge Tracing? EDM 2016 - [i3]Mohammad Khajah, Robert V. Lindsey, Michael C. Mozer:
How deep is knowledge tracing? CoRR abs/1604.02416 (2016) - [i2]Ronald T. Kneusel, Michael C. Mozer:
Improving Human-Machine Cooperative Visual Search With Soft Highlighting. CoRR abs/1612.08117 (2016) - 2015
- [c56]Nicole Beckage, Michael Mozer, Eliana Colunga:
Predicting a Child's Trajectory of Lexical Acquisition. CogSci 2015 - [i1]Karl Ridgeway, Jake Snell, Brett Roads, Richard S. Zemel, Michael C. Mozer:
Learning to generate images with perceptual similarity metrics. CoRR abs/1511.06409 (2015) - 2014
- [j19]Mohammad Khajah, Robert V. Lindsey, Michael C. Mozer:
Maximizing Students' Retention via Spaced Review: Practical Guidance From Computational Models of Memory. Top. Cogn. Sci. 6(1): 157-169 (2014) - [c55]Mohammad Khajah, Rowan Wing, Robert V. Lindsey, Michael Mozer:
Integrating latent-factor and knowledge-tracing models to predict individual differences in learning. EDM 2014: 99-106 - [c54]Robert V. Lindsey, Mohammad Khajah, Michael C. Mozer:
Automatic Discovery of Cognitive Skills to Improve the Prediction of Student Learning. NIPS 2014: 1386-1394 - [c53]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 - 2013
- [c52]Mohammad Khajah, Robert V. Lindsey, Michael Mozer:
Maximizing Students' Retention Via Spaced Review: Practical Guidance From Computational Models Of Memory. CogSci 2013 - [c51]Robert V. Lindsey, Michael Mozer, William J. Huggins, Harold Pashler:
Optimizing Instructional Policies. NIPS 2013: 2778-2786 - 2012
- [j18]Anup Doshi, Cuong Tran, Matthew H. Wilder, Michael C. Mozer, Mohan M. Trivedi:
Sequential Dependencies in Driving. Cogn. Sci. 36(5): 948-963 (2012) - 2011
- [c50]Benjamin Link, Brittany Ann Kos, Tor D. Wager, Michael Mozer:
Past Experience Influences Judgment of Pain: Prediction of Sequential Dependencies. CogSci 2011 - [c49]Michael C. Mozer, Benjamin Link, Harold Pashler:
An Unsupervised Decontamination Procedure For Improving The Reliability Of Human Judgments. NIPS 2011: 1791-1799 - 2010
- [c48]Michael Mozer, Harold Pashler, Matthew H. Wilder, Robert V. Lindsey, Matt Jones, Michael Jones:
Improving Human Judgments by Decontaminating Sequential Dependencies. NIPS 2010: 1705-1713
2000 – 2009
- 2009
- [c47]