Jasmine Collins

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 20

Top Topics

Three Dimensional Objects

Computational Models

Top Venues

Publications

Eliza Kosoy, David M. Chan, Adrian Liu, Jasmine Collins, Jessica B. Hamrick, Sandy Han Huang, Nan Rosemary Ke, Emily Rose Reagan, John F. Canny, Alison Gopnik
Towards Understanding How Machines Can Learn Causal Overhypotheses. CogSci (2023)
Aaron Gokaslan, A. Feder Cooper, Jasmine Collins, Landan Seguin, Austin Jacobson, Mihir Patel, Jonathan Frankle, Cory Stephenson, Volodymyr Kuleshov
CommonCanvas: An Open Diffusion Model Trained with Creative-Commons Images. CoRR (2023)
Rui Guo, Jasmine Collins, Oscar de Lima, Andrew Owens
GANmouflage: 3D Object Nondetection with Texture Fields. CVPR (2023)
Jasmine Collins, Anqi Liang, Jitendra Malik, Hao Zhang, Frédéric Devernay
T-Net: Category-Agnostic 3D Articulation Transfer from Single Image. CoRR (2023)
Eunice Yiu, Jasmine Collins, Alison Gopnik
Three-Dimensional Object Completion in Humans and Computational Models. CogSci (2022)
Eliza Kosoy, David M. Chan, Adrian Liu, Jasmine Collins, Bryanna Kaufmann, Sandy Han Huang, Jessica B. Hamrick, John F. Canny, Nan Rosemary Ke, Alison Gopnik
Towards Understanding How Machines Can Learn Causal Overhypotheses. CoRR (2022)
Jasmine Collins, Shubham Goel, Kenan Deng, Achleshwar Luthra, Leon Xu, Erhan Gundogdu, Xi Zhang, Tomas F. Yago Vicente, Thomas Dideriksen, Himanshu Arora, Matthieu Guillaumin, Jitendra Malik
ABO: Dataset and Benchmarks for Real-World 3D Object Understanding. CVPR (2022)
Eliza Kosoy, Adrian Liu, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Nan Rosemary Ke, Sandy H. Huang, Bryanna Kaufmann, John F. Canny, Alison Gopnik
Learning Causal Overhypotheses through Exploration in Children and Computational Models. CoRR (2022)
Eliza Kosoy, Adrian Liu, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Sandy Han Huang, Nan Rosemary Ke, Bryanna Kaufmann, Alison Gopnik
Learning Causal Overhypotheses through Exploration in Children and Computational Models. CogSci (2022)
Eliza Kosoy, Adrian Liu, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Nan Rosemary Ke, Sandy H. Huang, Bryanna Kaufmann, John F. Canny, Alison Gopnik
Learning Causal Overhypotheses through Exploration in Children and Computational Models. CLeaR (2022)
Rui Guo, Jasmine Collins, Oscar de Lima, Andrew Owens
GANmouflage: 3D Object Nondetection with Texture Fields. CoRR (2022)
Jasmine Collins, Shubham Goel, Achleshwar Luthra, Leon Xu, Kenan Deng, Xi Zhang, Tomas F. Yago Vicente, Himanshu Arora, Thomas Dideriksen, Matthieu Guillaumin, Jitendra Malik
ABO: Dataset and Benchmarks for Real-World 3D Object Understanding. CoRR (2021)
Eliza Kosoy, Jasmine Collins, David M. Chan, Deepak Pathak, Pulkit Agrawal, Alison Gopnik
Exploring Exploration: Comparing Children with Agents in Unified Exploration Environments. CogSci (2020)
Eliza Kosoy, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Sandy H. Huang, Alison Gopnik, John F. Canny
Exploring Exploration: Comparing Children with RL Agents in Unified Environments. CoRR (2020)
Jasmine Collins, Johannes Ballé, Jonathon Shlens
Accelerating Training of Deep Neural Networks with a Standardization Loss. CoRR (2019)
Jasmine Collins, Jascha Sohl-Dickstein, David Sussillo
Capacity and Trainability in Recurrent Neural Networks. ICLR (Poster) (2017)
Jasmine Collins, Jascha Sohl-Dickstein, David Sussillo
Capacity and Trainability in Recurrent Neural Networks. CoRR (2016)
Jocelyn Sunseri, Matthew Ragoza, Jasmine Collins, David Ryan Koes
A D3R prospective evaluation of machine learning for protein-ligand scoring. J. Comput. Aided Mol. Des. 30 (9) (2016)
Kendall G. Byler, Jasmine Collins, Ifedayo Victor Ogungbe, William N. Setzer
Alphavirus protease inhibitors from natural sources: A homology modeling and molecular docking investigation. Comput. Biol. Chem. 64 (2016)
Akosua Busia, Jasmine Collins, Navdeep Jaitly
Protein Secondary Structure Prediction Using Deep Multi-scale Convolutional Neural Networks and Next-Step Conditioning. CoRR (2016)