Daniel L. K. Yamins

62 papers A* 12B 6Journal 41Unranked 3
YearRankTypeTitle / Venue / Authors
2025 J jnl
3D Scene Understanding Through Local Random Access Sequence Modeling.
CoRR
Wanhee Lee, Klemen Kotar, Rahul Mysore Venkatesh, Jared Watrous, Honglin Chen, Khai Loong Aw, Daniel L. K. Yamins
2025 J jnl
Autoregressive Flow Matching for Motion Prediction.
CoRR
Johnathan Xie, Stefan Stojanov, Cristóbal Eyzaguirre, Daniel L. K. Yamins, Jiajun Wu
2025 A* conf
Hypothetical Minds: Scaffolding Theory of Mind for Multi-Agent Tasks with Large Language Models.
ICLR
Logan Matthew Cross, Violet Xiang, Agam Bhatia, Daniel L. K. Yamins, Nick Haber
2025 J jnl
Representing Speech Through Autoregressive Prediction of Cochlear Tokens.
CoRR
Greta Tuckute, Klemen Kotar, Evelina Fedorenko, Daniel L. K. Yamins
2025 J jnl
Self-Supervised Learning of Motion Concepts by Optimizing Counterfactuals.
CoRR
Stefan Stojanov, David Wendt, Seungwoo Kim, Rahul Mysore Venkatesh, Kevin T. Feigelis, Jiajun Wu, Daniel L. K. Yamins
2025 J jnl
Taming generative video models for zero-shot optical flow extraction.
CoRR
Seungwoo Kim, Khai Loong Aw, Klemen Kotar, Cristóbal Eyzaguirre, Wanhee Lee, Yunong Liu, Jared Watrous, Stefan Stojanov, Juan Carlos Niebles, Jiajun Wu, Daniel L. K. Yamins
2025 J jnl
Understanding Human Limits in Pattern Recognition: A Computational Model of Sequential Reasoning in Rock, Paper, Scissors.
CoRR
Logan Matthew Cross, Erik Brockbank, Tobias Gerstenberg, Judith E. Fan, Daniel L. K. Yamins, Nick Haber
2025 J jnl
Validating Generative Agent-Based Models of Social Norm Enforcement: From Replication to Novel Predictions.
CoRR
Logan Matthew Cross, Nick Haber, Daniel L. K. Yamins
2025 J jnl
Weakly-Supervised Learning of Dense Functional Correspondences.
CoRR
Stefan Stojanov, Linan Zhao, Yunzhi Zhang, Daniel L. K. Yamins, Jiajun Wu
2024 J jnl
Hypothetical Minds: Scaffolding Theory of Mind for Multi-Agent Tasks with Large Language Models.
CoRR
Logan Matthew Cross, Violet Xiang, Agam Bhatia, Daniel L. K. Yamins, Nick Haber
2024 J jnl
The BabyView dataset: High-resolution egocentric videos of infants' and young children's everyday experiences.
CoRR
Bria Long, Violet Xiang, Stefan Stojanov, Robert Z. Sparks, Zi Yin, Grace E. Keene, Alvin Wei Ming Tan, Steven Y. Feng, Chengxu Zhuang, Virginia A. Marchman, Daniel L. K. Yamins, Michael C. Frank
2024 J jnl
The Limiting Dynamics of SGD: Modified Loss, Phase-Space Oscillations, and Anomalous Diffusion.
Neural Comput.
Daniel Kunin, Javier Sagastuy-Breña, Lauren E. Gillespie, Eshed Margalit, Hidenori Tanaka, Surya Ganguli, Daniel L. K. Yamins
2024 — conf
Understanding Physical Dynamics with Counterfactual World Modeling.
ECCV (24)
Rahul Mysore Venkatesh, Honglin Chen, Kevin T. Feigelis, Daniel M. Bear, Khaled Jedoui, Klemen Kotar, Felix J. Binder, Wanhee Lee, Sherry Liu, Kevin A. Smith, Judith E. Fan, Daniel L. K. Yamins
2024 J jnl
Unsupervised 3D Scene Representation Learning via Movable Object Inference.
Trans. Mach. Learn. Res.
Honglin Chen, Wanhee Lee, Hong-Xing Yu, Rahul Mysore Venkatesh, Joshua B. Tenenbaum, Daniel Bear, Jiajun Wu, Daniel L. K. Yamins
2023 J jnl
3D-IntPhys: Towards More Generalized 3D-grounded Visual Intuitive Physics under Challenging Scenes.
CoRR
Haotian Xue, Antonio Torralba, Joshua B. Tenenbaum, Daniel L. K. Yamins, Yunzhu Li, Hsiao-Yu Tung
2023 B conf
Advancing Cognitive Science and AI with Cognitive-AI Benchmarking.
CogSci
Felix Jedidja Binder, Logan Matthew Cross, Yoni Friedman, Robert D. Hawkins, Daniel L. K. Yamins, Judith E. Fan
2023 J jnl
Are These the Same Apple? Comparing Images Based on Object Intrinsics.
CoRR
Klemen Kotar, Stephen Tian, Hong-Xing Yu, Daniel L. K. Yamins, Jiajun Wu
2023 J jnl
Counterfactual World Modeling for Physical Dynamics Understanding.
CoRR
Rahul Mysore Venkatesh, Honglin Chen, Kevin T. Feigelis, Daniel M. Bear, Khaled Jedoui, Klemen Kotar, Felix J. Binder, Wanhee Lee, Sherry Liu, Kevin A. Smith, Judith E. Fan, Daniel L. K. Yamins
2023 B conf
Developmental Curiosity and Social Interaction in Virtual Agents.
CogSci
Chris Doyle, Sarah Shader, Michelle Lau, Megumi Sano, Daniel L. K. Yamins, Nick Haber
2023 J jnl
Developmental Curiosity and Social Interaction in Virtual Agents.
CoRR
Chris Doyle, Sarah Shader, Michelle Lau, Megumi Sano, Daniel L. K. Yamins, Nick Haber
2023 J jnl
Measuring and Modeling Physical Intrinsic Motivation.
CoRR
Julio Martinez, Felix J. Binder, Haoliang Wang, Nick Haber, Judith E. Fan, Daniel L. K. Yamins
2023 J jnl
Mouse visual cortex as a limited resource system that self-learns an ecologically-general representation.
PLoS Comput. Biol.
Aran Nayebi, Nathan C. L. Kong, Chengxu Zhuang, Justin L. Gardner, Anthony M. Norcia, Daniel L. K. Yamins
2023 J jnl
Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties.
CoRR
Hsiao-Yu Tung, Mingyu Ding, Zhenfang Chen, Daniel Bear, Chuang Gan, Joshua B. Tenenbaum, Daniel L. K. Yamins, Judith E. Fan, Kevin A. Smith
2023 J jnl
Unifying (Machine) Vision via Counterfactual World Modeling.
CoRR
Daniel M. Bear, Kevin T. Feigelis, Honglin Chen, Wanhee Lee, Rahul Mysore Venkatesh, Klemen Kotar, Alex Durango, Daniel L. K. Yamins
2022 A* conf
FAR: End-to-End Vibrotactile Distributed System Designed to Facilitate Affect Regulation in Children Diagnosed with Autism Spectrum Disorder Through Slow Breathing.
CHI
Pardis Miri, Mehul Arora, Aman Malhotra, Robert Flory, Stephanie Hu, Ashley Lowber, Ishan Goyal, Jacqueline Nguyen, John P. Hegarty, Marlo D. Kohn, David Schneider, Heather Culbertson, Daniel L. K. Yamins, Lawrence Fung, Antonio Hardan, James J. Gross, Keith Marzullo
2022 J jnl
Recurrent Connections in the Primate Ventral Visual Stream Mediate a Trade-Off Between Task Performance and Network Size During Core Object Recognition.
Neural Comput.
Aran Nayebi, Javier Sagastuy-Breña, Daniel M. Bear, Kohitij Kar, Jonas Kubilius, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins
2022 A* conf
The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark Towards Physically Realistic Embodied AI.
ICRA
Chuang Gan, Siyuan Zhou, Jeremy Schwartz, Seth Alter, Abhishek Bhandwaldar, Dan Gutfreund, Daniel L. K. Yamins, James J. DiCarlo, Josh H. McDermott, Antonio Torralba, Joshua B. Tenenbaum
2022 — conf
Unsupervised Segmentation in Real-World Images via Spelke Object Inference.
ECCV (29)
Honglin Chen, Rahul Mysore Venkatesh, Yoni Friedman, Jiajun Wu, Joshua B. Tenenbaum, Daniel L. K. Yamins, Daniel M. Bear
2022 J jnl
Unsupervised Segmentation in Real-World Images via Spelke Object Inference.
CoRR
Honglin Chen, Rahul Mysore Venkatesh, Yoni Friedman, Jiajun Wu, Joshua B. Tenenbaum, Daniel L. K. Yamins, Daniel M. Bear
2021 A* conf
Explaining heterogeneity in medial entorhinal cortex with task-driven neural networks.
NeurIPS
Aran Nayebi, Alexander Attinger, Malcolm Campbell, Kiah Hardcastle, Isabel Low, Caitlin S. Mallory, Gabriel Mel, Ben Sorscher, Alex H. Williams, Surya Ganguli, Lisa M. Giocomo, Daniel L. K. Yamins
2021 B conf
Measuring and predicting variation in the interestingness of physical structures.
CogSci
Cameron Holdaway, Daniel M. Bear, Samaher Radwan, Michael C. Frank, Daniel L. K. Yamins, Judith E. Fan
2021 A* conf
Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics.
ICLR
Daniel Kunin, Javier Sagastuy-Breña, Surya Ganguli, Daniel L. K. Yamins, Hidenori Tanaka
2021 J jnl
Physion: Evaluating Physical Prediction from Vision in Humans and Machines.
CoRR
Daniel M. Bear, Elias Wang, Damian Mrowca, Felix J. Binder, Hsiau-Yu Fish Tung, R. T. Pramod, Cameron Holdaway, Sirui Tao, Kevin A. Smith, Fan-Yun Sun, Li Fei-Fei, Nancy Kanwisher, Joshua B. Tenenbaum, Daniel L. K. Yamins, Judith E. Fan
2021 B conf
Predicting children's and adults' preferences in physical interactions via physics simulation.
CogSci
George Kachergis, Samaher Radwan, Bria Long, Judith E. Fan, Michael Lingelbach, Daniel M. Bear, Daniel L. K. Yamins, Michael C. Frank
2021 J jnl
Rethinking the limiting dynamics of SGD: modified loss, phase space oscillations, and anomalous diffusion.
CoRR
Daniel Kunin, Javier Sagastuy-Breña, Lauren E. Gillespie, Eshed Margalit, Hidenori Tanaka, Surya Ganguli, Daniel L. K. Yamins
2021 J jnl
The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark for Physically Realistic Embodied AI.
CoRR
Chuang Gan, Siyuan Zhou, Jeremy Schwartz, Seth Alter, Abhishek Bhandwaldar, Dan Gutfreund, Daniel L. K. Yamins, James J. DiCarlo, Josh H. McDermott, Antonio Torralba, Joshua B. Tenenbaum
2021 J jnl
Unsupervised neural network models of the ventral visual stream.
Proc. Natl. Acad. Sci. USA
Chengxu Zhuang, Siming Yan, Aran Nayebi, Martin Schrimpf, Michael C. Frank, James J. DiCarlo, Daniel L. K. Yamins
2020 A* conf
Identifying Learning Rules From Neural Network Observables.
NeurIPS
Aran Nayebi, Sanjana Srivastava, Surya Ganguli, Daniel L. K. Yamins
2020 J jnl
Identifying Learning Rules From Neural Network Observables.
CoRR
Aran Nayebi, Sanjana Srivastava, Surya Ganguli, Daniel L. K. Yamins
2020 A* conf
Learning Physical Graph Representations from Visual Scenes.
NeurIPS
Daniel Bear, Chaofei Fan, Damian Mrowca, Yunzhu Li, Seth Alter, Aran Nayebi, Jeremy Schwartz, Li Fei-Fei, Jiajun Wu, Josh Tenenbaum, Daniel L. K. Yamins
2020 J jnl
Learning Physical Graph Representations from Visual Scenes.
CoRR
Daniel M. Bear, Chaofei Fan, Damian Mrowca, Yunzhu Li, Seth Alter, Aran Nayebi, Jeremy Schwartz, Li Fei-Fei, Jiajun Wu, Joshua B. Tenenbaum, Daniel L. K. Yamins
2020 B conf
Learning in Social Environments with Curious Neural Agents.
CogSci
Megumi Sano, Julian De Freitas, Nick Haber, Daniel L. K. Yamins
2020 J jnl
Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics.
CoRR
Daniel Kunin, Javier Sagastuy-Breña, Surya Ganguli, Daniel L. K. Yamins, Hidenori Tanaka
2020 A* conf
Pruning neural networks without any data by iteratively conserving synaptic flow.
NeurIPS
Hidenori Tanaka, Daniel Kunin, Daniel L. K. Yamins, Surya Ganguli
2020 J jnl
Pruning neural networks without any data by iteratively conserving synaptic flow.
CoRR
Hidenori Tanaka, Daniel Kunin, Daniel L. K. Yamins, Surya Ganguli
2020 J jnl
ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation.
CoRR
Chuang Gan, Jeremy Schwartz, Seth Alter, Martin Schrimpf, James Traer, Julian De Freitas, Jonas Kubilius, Abhishek Bhandwaldar, Nick Haber, Megumi Sano, Kuno Kim, Elias Wang, Damian Mrowca, Michael Lingelbach, Aidan Curtis, Kevin T. Feigelis, Daniel M. Bear, Dan Gutfreund, David D. Cox, James J. DiCarlo, Josh H. McDermott, Joshua B. Tenenbaum, Daniel L. K. Yamins
2020 J jnl
Two Routes to Scalable Credit Assignment without Weight Symmetry.
CoRR
Daniel Kunin, Aran Nayebi, Javier Sagastuy-Breña, Surya Ganguli, Jonathan M. Bloom, Daniel L. K. Yamins
2020 J jnl
Visual Grounding of Learned Physical Models.
CoRR
Yunzhu Li, Toru Lin, Kexin Yi, Daniel Bear, Daniel L. K. Yamins, Jiajun Wu, Joshua B. Tenenbaum, Antonio Torralba
2019 A* conf
Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs.
NeurIPS
Jonas Kubilius, Martin Schrimpf, Ha Hong, Najib J. Majaj, Rishi Rajalingham, Elias B. Issa, Kohitij Kar, Pouya Bashivan, Jonathan Prescott-Roy, Kailyn Schmidt, Aran Nayebi, Daniel Bear, Daniel L. K. Yamins, James J. DiCarlo
2019 J jnl
Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs.
CoRR
Jonas Kubilius, Martin Schrimpf, Ha Hong, Najib J. Majaj, Rishi Rajalingham, Elias B. Issa, Kohitij Kar, Pouya Bashivan, Jonathan Prescott-Roy, Kailyn Schmidt, Aran Nayebi, Daniel Bear, Daniel L. K. Yamins, James J. DiCarlo
2018 J jnl
Common Object Representations for Visual Production and Recognition.
Cogn. Sci.
Judith E. Fan, Daniel L. K. Yamins, Nicholas B. Turk-Browne
2018 B conf
Emergence of Structured Behaviors from Curiosity-Based Intrinsic Motivation.
CogSci
Nick Haber, Damian Mrowca, Li Fei-Fei, Daniel L. K. Yamins
2018 J jnl
Emergence of Structured Behaviors from Curiosity-Based Intrinsic Motivation.
CoRR
Nick Haber, Damian Mrowca, Li Fei-Fei, Daniel L. K. Yamins
2018 J jnl
Flexible Neural Representation for Physics Prediction.
CoRR
Damian Mrowca, Chengxu Zhuang, Elias Wang, Nick Haber, Li Fei-Fei, Joshua B. Tenenbaum, Daniel L. K. Yamins
2018 A* conf
Flexible neural representation for physics prediction.
NeurIPS
Damian Mrowca, Chengxu Zhuang, Elias Wang, Nick Haber, Li Fei-Fei, Josh Tenenbaum, Daniel L. K. Yamins
2018 A* conf
Learning to Play With Intrinsically-Motivated, Self-Aware Agents.
NeurIPS
Nick Haber, Damian Mrowca, Stephanie Wang, Li Fei-Fei, Daniel L. K. Yamins
2018 J jnl
Learning to Play with Intrinsically-Motivated Self-Aware Agents.
CoRR
Nick Haber, Damian Mrowca, Li Fei-Fei, Daniel L. K. Yamins
2018 — conf
Modular Continual Learning in a Unified Visual Environment.
ICLR (Poster)
Kevin T. Feigelis, Blue Sheffer, Daniel L. K. Yamins
2018 A* conf
Task-Driven Convolutional Recurrent Models of the Visual System.
NeurIPS
Aran Nayebi, Daniel Bear, Jonas Kubilius, Kohitij Kar, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins
2018 J jnl
Task-Driven Convolutional Recurrent Models of the Visual System.
CoRR
Aran Nayebi, Daniel Bear, Jonas Kubilius, Kohitij Kar, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins
2017 J jnl
A Useful Motif for Flexible Task Learning in an Embodied Two-Dimensional Visual Environment.
CoRR
Kevin T. Feigelis, Daniel L. K. Yamins
2017 J jnl
Modular Continual Learning in a Unified Visual Environment.
CoRR
Kevin T. Feigelis, Blue Sheffer, Daniel L. K. Yamins