Daniel L. K. Yamins

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 44

Top Topics

Physical Models

Intrinsic Motivation

Unsupervised Segmentation

Top Venues

Publications

Bria Long, Violet Xiang, Stefan Stojanov, Robert Z. Sparks, Zi Yin, Grace E. Keene, Alvin W. M. Tan, Steven Y. Feng, Chengxu Zhuang, Virginia A. Marchman, Daniel L. K. Yamins, Michael C. Frank
The BabyView dataset: High-resolution egocentric videos of infants' and young children's everyday experiences. CoRR (2024)
Honglin Chen, Wanhee Lee, Hong-Xing Yu, Rahul Mysore Venkatesh, Joshua B. Tenenbaum, Daniel Bear, Jiajun Wu, Daniel L. K. Yamins
Unsupervised 3D Scene Representation Learning via Movable Object Inference. Trans. Mach. Learn. Res. 2024 (2024)
Logan Cross, Violet Xiang, Agam Bhatia, Daniel L. K. Yamins, Nick Haber
Hypothetical Minds: Scaffolding Theory of Mind for Multi-Agent Tasks with Large Language Models. CoRR (2024)
Daniel Kunin, Javier Sagastuy-Breña, Lauren Gillespie, Eshed Margalit, Hidenori Tanaka, Surya Ganguli, Daniel L. K. Yamins
The Limiting Dynamics of SGD: Modified Loss, Phase-Space Oscillations, and Anomalous Diffusion. Neural Comput. 36 (1) (2024)
Felix Jedidja Binder, Logan Matthew Cross, Yoni Friedman, Robert D. Hawkins, Daniel L. K. Yamins, Judith E. Fan
Advancing Cognitive Science and AI with Cognitive-AI Benchmarking. CogSci (2023)
Rahul Venkatesh, Honglin Chen, Kevin T. Feigelis, Daniel M. Bear, Khaled Jedoui, Klemen Kotar, Felix Binder, Wanhee Lee, Sherry Liu, Kevin A. Smith, Judith E. Fan, Daniel L. K. Yamins
Counterfactual World Modeling for Physical Dynamics Understanding. CoRR (2023)
Hsiao-Yu Tung, Mingyu Ding, Zhenfang Chen, Daniel Bear, Chuang Gan, Joshua B. Tenenbaum, Daniel L. K. Yamins, Judith E. Fan, Kevin A. Smith
Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties. CoRR (2023)
Aran Nayebi, Nathan C. L. Kong, Chengxu Zhuang, Justin L. Gardner, Anthony M. Norcia, Daniel L. K. Yamins
Mouse visual cortex as a limited resource system that self-learns an ecologically-general representation. PLoS Comput. Biol. 19 (10) (2023)
Daniel M. Bear, Kevin T. Feigelis, Honglin Chen, Wanhee Lee, Rahul Venkatesh, Klemen Kotar, Alex Durango, Daniel L. K. Yamins
Unifying (Machine) Vision via Counterfactual World Modeling. CoRR (2023)
Haotian Xue, Antonio Torralba, Joshua B. Tenenbaum, Daniel L. K. Yamins, Yunzhu Li, Hsiao-Yu Tung
3D-IntPhys: Towards More Generalized 3D-grounded Visual Intuitive Physics under Challenging Scenes. CoRR (2023)
Klemen Kotar, Stephen Tian, Hong-Xing Yu, Daniel L. K. Yamins, Jiajun Wu
Are These the Same Apple? Comparing Images Based on Object Intrinsics. CoRR (2023)
Chris Doyle, Sarah Shader, Michelle Lau, Megumi Sano, Daniel L. K. Yamins, Nick Haber
Developmental Curiosity and Social Interaction in Virtual Agents. CoRR (2023)
Chris Doyle, Sarah Shader, Michelle Lau, Megumi Sano, Daniel L. K. Yamins, Nick Haber
Developmental Curiosity and Social Interaction in Virtual Agents. CogSci (2023)
Julio Martinez, Felix J. Binder, Haoliang Wang, Nick Haber, Judith E. Fan, Daniel L. K. Yamins
Measuring and Modeling Physical Intrinsic Motivation. CoRR (2023)
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
The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark Towards Physically Realistic Embodied AI. ICRA (2022)
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
FAR: End-to-End Vibrotactile Distributed System Designed to Facilitate Affect Regulation in Children Diagnosed with Autism Spectrum Disorder Through Slow Breathing. CHI (2022)
Aran Nayebi, Javier Sagastuy-Breña, Daniel M. Bear, Kohitij Kar, Jonas Kubilius, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins
Recurrent Connections in the Primate Ventral Visual Stream Mediate a Trade-Off Between Task Performance and Network Size During Core Object Recognition. Neural Comput. 34 (8) (2022)
Honglin Chen, Rahul Venkatesh, Yoni Friedman, Jiajun Wu, Joshua B. Tenenbaum, Daniel L. K. Yamins, Daniel M. Bear
Unsupervised Segmentation in Real-World Images via Spelke Object Inference. CoRR (2022)
Honglin Chen, Rahul Venkatesh, Yoni Friedman, Jiajun Wu, Joshua B. Tenenbaum, Daniel L. K. Yamins, Daniel M. Bear
Unsupervised Segmentation in Real-World Images via Spelke Object Inference. ECCV (24) (2022)
Cameron Holdaway, Daniel M. Bear, Samaher Radwan, Michael C. Frank, Daniel L. K. Yamins, Judith E. Fan
Measuring and predicting variation in the interestingness of physical structures. CogSci (2021)
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
Explaining heterogeneity in medial entorhinal cortex with task-driven neural networks. NeurIPS (2021)
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
Physion: Evaluating Physical Prediction from Vision in Humans and Machines. CoRR (2021)
Daniel Kunin, Javier Sagastuy-Breña, Lauren Gillespie, Eshed Margalit, Hidenori Tanaka, Surya Ganguli, Daniel L. K. Yamins
Rethinking the limiting dynamics of SGD: modified loss, phase space oscillations, and anomalous diffusion. CoRR (2021)
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
The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark for Physically Realistic Embodied AI. CoRR (2021)
George Kachergis, Samaher Radwan, Bria Long, Judith E. Fan, Michael Lingelbach, Daniel M. Bear, Daniel L. K. Yamins, Michael C. Frank
Predicting children's and adults' preferences in physical interactions via physics simulation. CogSci (2021)
Chengxu Zhuang, Siming Yan, Aran Nayebi, Martin Schrimpf, Michael C. Frank, James J. DiCarlo, Daniel L. K. Yamins
Unsupervised neural network models of the ventral visual stream. Proc. Natl. Acad. Sci. USA 118 (3) (2021)
Daniel Kunin, Aran Nayebi, Javier Sagastuy-Breña, Surya Ganguli, Jonathan M. Bloom, Daniel L. K. Yamins
Two Routes to Scalable Credit Assignment without Weight Symmetry. CoRR (2020)
Daniel Kunin, Javier Sagastuy-Breña, Surya Ganguli, Daniel L. K. Yamins, Hidenori Tanaka
Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics. CoRR (2020)
Megumi Sano, Julian De Freitas, Nick Haber, Daniel L. K. Yamins
Learning in Social Environments with Curious Neural Agents. CogSci (2020)
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
ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation. CoRR (2020)
Yunzhu Li, Toru Lin, Kexin Yi, Daniel Bear, Daniel L. K. Yamins, Jiajun Wu, Joshua B. Tenenbaum, Antonio Torralba
Visual Grounding of Learned Physical Models. CoRR (2020)
Hidenori Tanaka, Daniel Kunin, Daniel L. K. Yamins, Surya Ganguli
Pruning neural networks without any data by iteratively conserving synaptic flow. CoRR (2020)
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
Learning Physical Graph Representations from Visual Scenes. CoRR (2020)
Aran Nayebi, Sanjana Srivastava, Surya Ganguli, Daniel L. K. Yamins
Identifying Learning Rules From Neural Network Observables. CoRR (2020)
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
Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs. CoRR (2019)
Nick Haber, Damian Mrowca, Li Fei-Fei, Daniel L. K. Yamins
Emergence of Structured Behaviors from Curiosity-Based Intrinsic Motivation. CoRR (2018)
Damian Mrowca, Chengxu Zhuang, Elias Wang, Nick Haber, Li Fei-Fei, Joshua B. Tenenbaum, Daniel L. K. Yamins
Flexible Neural Representation for Physics Prediction. CoRR (2018)
Kevin T. Feigelis, Blue Sheffer, Daniel L. K. Yamins
Modular Continual Learning in a Unified Visual Environment. ICLR (Poster) (2018)
Nick Haber, Damian Mrowca, Li Fei-Fei, Daniel L. K. Yamins
Emergence of Structured Behaviors from Curiosity-Based Intrinsic Motivation. CogSci (2018)
Aran Nayebi, Daniel Bear, Jonas Kubilius, Kohitij Kar, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins
Task-Driven Convolutional Recurrent Models of the Visual System. CoRR (2018)
Nick Haber, Damian Mrowca, Li Fei-Fei, Daniel L. K. Yamins
Learning to Play with Intrinsically-Motivated Self-Aware Agents. CoRR (2018)
Judith E. Fan, Daniel L. K. Yamins, Nicholas B. Turk-Browne
Common Object Representations for Visual Production and Recognition. Cogn. Sci. 42 (8) (2018)
Kevin T. Feigelis, Daniel L. K. Yamins
A Useful Motif for Flexible Task Learning in an Embodied Two-Dimensional Visual Environment. CoRR (2017)
Kevin T. Feigelis, Blue Sheffer, Daniel L. K. Yamins
Modular Continual Learning in a Unified Visual Environment. CoRR (2017)