Daniel Bear

According to our database, Daniel Bear authored at least 16 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Counterfactual World Modeling for Physical Dynamics Understanding.

Rahul 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

CoRR, 2023

Unifying (Machine) Vision via Counterfactual World Modeling.

Daniel M. Bear, Kevin T. Feigelis, Honglin Chen, Wanhee Lee, Rahul Venkatesh, Klemen Kotar, Alex Durango, Daniel L. K. Yamins

CoRR, 2023

Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties.

Hsiao-Yu Tung, Mingyu Ding, Zhenfang Chen, Daniel Bear, Chuang Gan, Josh Tenenbaum, Dan Yamins, Judith E. Fan, Kevin A. Smith

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Recurrent Connections in the Primate Ventral Visual Stream Mediate a Trade-Off Between Task Performance and Network Size During Core Object Recognition.

Aran Nayebi, Javier Sagastuy-Breña, Daniel M. Bear, Kohitij Kar, Jonas Kubilius, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins

Neural Comput., 2022

Unsupervised Segmentation in Real-World Images via Spelke Object Inference.

Honglin Chen, Rahul Venkatesh, Yoni Friedman, Jiajun Wu, Joshua B. Tenenbaum, Daniel L. K. Yamins, Daniel M. Bear

Proceedings of the Computer Vision - ECCV 2022, 2022

Benchmarking mid-level vision with texture-defined 3D objects.

Yoni Friedman, Thomas P. O'Connell, Max H. Siegel, Daniel M. Bear, Tuan Anh Le, Bernhard Egger, Josh Tenenbaum

Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022

2021

Physion: Evaluating Physical Prediction from Vision in Humans and Machines.

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

CoRR, 2021

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation.

Chuang Gan, Jeremy Schwartz, Seth Alter, Damian Mrowca, Martin Schrimpf, James Traer, Julian De Freitas, Jonas Kubilius, Abhishek Bhandwaldar, Nick Haber, Megumi Sano, Kuno Kim, Elias Wang, Michael Lingelbach, Aidan Curtis, Kevin T. Feigelis, Daniel Bear, Dan Gutfreund, David D. Cox, Antonio Torralba, James J. DiCarlo, Josh Tenenbaum, Josh H. McDermott, Dan Yamins

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Physion: Evaluating Physical Prediction from Vision in Humans and Machines.

Daniel Bear, Elias Wang, Damian Mrowca, Felix J. Binder, Hsiao-Yu Tung, R. T. Pramod, Cameron Holdaway, Sirui Tao, Kevin A. Smith, Fan-Yun Sun, Fei-Fei Li, Nancy Kanwisher, Josh Tenenbaum, Dan Yamins, Judith E. Fan

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Predicting children's and adults' preferences in physical interactions via physics simulation.

George Kachergis, Samaher Radwan, Bria Long, Judith E. Fan, Michael Lingelbach, Daniel M. Bear, Daniel L. K. Yamins, Michael C. Frank

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

Measuring and predicting variation in the interestingness of physical structures.

Cameron Holdaway, Daniel M. Bear, Samaher Radwan, Michael C. Frank, Daniel L. K. Yamins, Judith E. Fan

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

2020

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation.

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

CoRR, 2020

Learning Physical Graph Representations from Visual Scenes.

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Visual Grounding of Learned Physical Models.

Yunzhu Li, Toru Lin, Kexin Yi, Daniel Bear, Daniel Yamins, Jiajun Wu, Joshua B. Tenenbaum, Antonio Torralba

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs.

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

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Task-Driven Convolutional Recurrent Models of the Visual System.

Aran Nayebi, Daniel Bear, Jonas Kubilius, Kohitij Kar, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018