Alphavirus protease inhibitors from natural sources: A homology modeling and molecular docking investigation. - Kendall G. Byler; Jasmine Collins; Ifedayo Victor Ogungbe; William N. Setzer (Comput. Biol. Chem., 2016)

Protein Secondary Structure Prediction Using Deep Multi-scale Convolutional Neural Networks and Next-Step Conditioning. - Akosua Busia; Jasmine Collins; Navdeep Jaitly (CoRR, 2016)

A D3R prospective evaluation of machine learning for protein-ligand scoring. - Jocelyn Sunseri; Matthew Ragoza; Jasmine Collins; David Ryan Koes (J. Comput. Aided Mol. Des., 2016)

Capacity and Trainability in Recurrent Neural Networks. - Jasmine Collins; Jascha Sohl-Dickstein; David Sussillo (ICLR (Poster), 2017)

Accelerating Training of Deep Neural Networks with a Standardization Loss. - Jasmine Collins; Johannes Ballé; Jonathon Shlens (CoRR, 2019)

Exploring Exploration: Comparing Children with Agents in Unified Exploration Environments. - Eliza Kosoy; Jasmine Collins; David M. Chan; Deepak Pathak; Pulkit Agrawal 001; Alison Gopnik (CogSci, 2020)

Exploring Exploration: Comparing Children with RL Agents in Unified Environments. - Eliza Kosoy; Jasmine Collins; David M. Chan; Jessica B. Hamrick; Sandy H. Huang; Alison Gopnik; John F. Canny (CoRR, 2020)

ABO: Dataset and Benchmarks for Real-World 3D Object Understanding. - Jasmine Collins; Shubham Goel 001; Achleshwar Luthra; Leon Xu; Kenan Deng 001; Xi Zhang; Tomas F. Yago Vicente; Himanshu Arora; Thomas Dideriksen; Matthieu Guillaumin; Jitendra Malik (CoRR, 2021)

Learning Causal Overhypotheses through Exploration in Children and Computational Models. - 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 (CLeaR, 2022)

Learning Causal Overhypotheses through Exploration in Children and Computational Models. - Eliza Kosoy; Adrian Liu; Jasmine Collins; David M. Chan; Jessica B. Hamrick; Sandy Han Huang; Nan Rosemary Ke; Bryanna Kaufmann; Alison Gopnik (CogSci, 2022)

Three-Dimensional Object Completion in Humans and Computational Models. - Eunice Yiu; Jasmine Collins; Alison Gopnik (CogSci, 2022)

ABO: Dataset and Benchmarks for Real-World 3D Object Understanding. - Jasmine Collins; Shubham Goel 001; Kenan Deng 001; Achleshwar Luthra; Leon Xu; Erhan Gundogdu; Xi Zhang; Tomas F. Yago Vicente; Thomas Dideriksen; Himanshu Arora; Matthieu Guillaumin; Jitendra Malik (CVPR, 2022)

Towards Understanding How Machines Can Learn Causal Overhypotheses. - 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 (CoRR, 2022)

Towards Understanding How Machines Can Learn Causal Overhypotheses. - 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 (CogSci, 2023)

GANmouflage: 3D Object Nondetection with Texture Fields. - Rui Guo; Jasmine Collins; Oscar de Lima; Andrew Owens (CVPR, 2023)

CA2T-Net: Category-Agnostic 3D Articulation Transfer from Single Image. - Jasmine Collins; Anqi Liang; Jitendra Malik; Hao Zhang 003; Frédéric Devernay (CoRR, 2023)

CommonCanvas: An Open Diffusion Model Trained with Creative-Commons Images. - Aaron Gokaslan; A. Feder Cooper; Jasmine Collins; Landan Seguin; Austin Jacobson; Mihir Patel; Jonathan Frankle; Cory Stephenson; Volodymyr Kuleshov (CoRR, 2023)

Bridging the Gap between Humans and Machines in 3D Object Perception - Jasmine Collins (2023)

Common Canvas: Open Diffusion Models Trained on Creative-Commons Images. - Aaron Gokaslan; A. Feder Cooper; Jasmine Collins; Landan Seguin; Austin Jacobson; Mihir Patel; Jonathan Frankle; Cory Stephenson; Volodymyr Kuleshov (CVPR, 2024)