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Towards Understanding How Machines Can Learn Causal Overhypotheses


Jun 16, 2022
Eliza Kosoy, David M. Chan, Adrian Liu, Jasmine Collins, Bryanna Kaufmann, Sandy Han Huang, Jessica B. Hamrick, John Canny, Nan Rosemary Ke, Alison Gopnik


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Learning Causal Overhypotheses through Exploration in Children and Computational Models


Feb 21, 2022
Eliza Kosoy, Adrian Liu, Jasmine Collins, David M Chan, Jessica B Hamrick, Nan Rosemary Ke, Sandy H Huang, Bryanna Kaufmann, John Canny, Alison Gopnik


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GANmouflage: 3D Object Nondetection with Texture Fields


Jan 18, 2022
Rui Guo, Jasmine Collins, Oscar de Lima, Andrew Owens


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ABO: Dataset and Benchmarks for Real-World 3D Object Understanding


Oct 12, 2021
Jasmine Collins, Shubham Goel, Achleshwar Luthra, Leon Xu, Kenan Deng, Xi Zhang, Tomas F. Yago Vicente, Himanshu Arora, Thomas Dideriksen, Matthieu Guillaumin, Jitendra Malik


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Exploring Exploration: Comparing Children with RL Agents in Unified Environments


May 06, 2020
Eliza Kosoy, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Sandy Huang, Alison Gopnik, John Canny

* Published as a workshop paper at "Bridging AI and Cognitive Science" (ICLR 2020) 

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Accelerating Training of Deep Neural Networks with a Standardization Loss


Mar 03, 2019
Jasmine Collins, Johannes Balle, Jonathon Shlens

* Technical report. Results presented at WiML 2018 

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Capacity and Trainability in Recurrent Neural Networks


Mar 03, 2017
Jasmine Collins, Jascha Sohl-Dickstein, David Sussillo

* Published as a conference paper at ICLR 2017 

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Protein Secondary Structure Prediction Using Deep Multi-scale Convolutional Neural Networks and Next-Step Conditioning


Nov 04, 2016
Akosua Busia, Jasmine Collins, Navdeep Jaitly

* 10 pages, 2 figures, submitted to RECOMB 2017 

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