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Daniel Bear
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2020 – today
- 2024
- [j2]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) - 2023
- [c11]Hsiao-Yu Tung, Mingyu Ding, Zhenfang Chen, Daniel Bear, Chuang Gan, Josh Tenenbaum, Dan Yamins, Judith E. Fan, Kevin A. Smith:
Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties. NeurIPS 2023 - [i10]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 abs/2306.01828 (2023) - [i9]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 abs/2306.15668 (2023) - [i8]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:
Counterfactual World Modeling for Physical Dynamics Understanding. CoRR abs/2312.06721 (2023) - 2022
- [j1]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): 1652-1675 (2022) - [c10]Yoni Friedman, Thomas P. O'Connell, Max H. Siegel, Daniel M. Bear, Tuan Anh Le, Bernhard Egger, Josh Tenenbaum:
Benchmarking mid-level vision with texture-defined 3D objects. CogSci 2022 - [c9]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 (29) 2022: 719-735 - [i7]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 abs/2205.08515 (2022) - 2021
- [c8]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 - [c7]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 - [c6]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:
Physion: Evaluating Physical Prediction from Vision in Humans and Machines. NeurIPS Datasets and Benchmarks 2021 - [c5]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:
ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation. NeurIPS Datasets and Benchmarks 2021 - [i6]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 abs/2106.08261 (2021) - 2020
- [c4]Yunzhu Li, Toru Lin, Kexin Yi, Daniel Bear, Daniel Yamins, Jiajun Wu, Joshua B. Tenenbaum, Antonio Torralba:
Visual Grounding of Learned Physical Models. ICML 2020: 5927-5936 - [c3]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:
Learning Physical Graph Representations from Visual Scenes. NeurIPS 2020 - [i5]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 abs/2004.13664 (2020) - [i4]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 abs/2006.12373 (2020) - [i3]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 abs/2007.04954 (2020)
2010 – 2019
- 2019
- [c2]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. NeurIPS 2019: 12785-12796 - [i2]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 abs/1909.06161 (2019) - 2018
- [c1]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. NeurIPS 2018: 5295-5306 - [i1]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 abs/1807.00053 (2018)
Coauthor Index
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last updated on 2024-08-10 00:31 CEST by the dblp team
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