Sharon Zhou

According to our database, Sharon Zhou authored at least 19 papers between 2016 and 2021.

Collaborative distances:

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

2021

On the evaluation of deep generative models.

Sharon Zhou

PhD thesis, 2021

Data augmentation with Mobius transformations.

Sharon Zhou, Jiequan Zhang, Hang Jiang, Torbjörn Lundh, Andrew Y. Ng

Mach. Learn. Sci. Technol., 2021

Evaluating the Disentanglement of Deep Generative Models through Manifold Topology.

Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y. Ng, Gunnar E. Carlsson, Stefano Ermon

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Establishing an evaluation metric to quantify climate change image realism.

Sharon Zhou, Alexandra Luccioni, Gautier Cosne, Michael S. Bernstein, Yoshua Bengio

Mach. Learn. Sci. Technol., 2020

ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery.

Jeremy Irvin, Hao Sheng, Neel Ramachandran, Sonja Johnson-Yu, Sharon Zhou, Kyle Story, Rose Rustowicz, Cooper Elsworth, Kemen Austin, Andrew Y. Ng

CoRR, 2020

Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models.

Eric Zelikman, Sharon Zhou, Jeremy Irvin, Cooper Raterink, Hao Sheng, Jack Kelly, Ram Rajagopal, Andrew Y. Ng, David Gagne

CoRR, 2020

CheXphoto: 10, 000+ Smartphone Photos and Synthetic Photographic Transformations of Chest X-rays for Benchmarking Deep Learning Robustness.

Nick A. Phillips, Pranav Rajpurkar, Mark Sabini, Rayan Krishnan, Sharon Zhou, Anuj Pareek, Nguyet Minh Phu, Chris Wang, Andrew Y. Ng, Matthew P. Lungren

CoRR, 2020

Evaluating the Disentanglement of Deep Generative Models through Manifold Topology.

Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y. Ng, Stefano Ermon

CoRR, 2020

CheXphoto: 10, 000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness.

Nick A. Phillips, Pranav Rajpurkar, Mark Sabini, Rayan Krishnan, Sharon Zhou, Anuj Pareek, Nguyet Minh Phu, Chris Wang, Mudit Jain, Du Nguyen Duong, Steven Q. H. Truong, Andrew Y. Ng, Matthew P. Lungren

Proceedings of the Machine Learning for Health Workshop, 2020

2019

Approximating Human Judgment of Generated Image Quality.

Y. Alex Kolchinski, Sharon Zhou, Shengjia Zhao, Mitchell L. Gordon, Stefano Ermon

CoRR, 2019

Countdown Regression: Sharp and Calibrated Survival Predictions.

Anand Avati, Tony Duan, Sharon Zhou, Kenneth Jung, Nigam H. Shah, Andrew Y. Ng

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models.

Sharon Zhou, Mitchell L. Gordon, Ranjay Krishna, Austin Narcomey, Li Fei-Fei, Michael S. Bernstein

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

HYPE: Human-eYe Perceptual Evaluation of Generative Models.

Sharon Zhou, Mitchell L. Gordon, Ranjay Krishna, Austin Narcomey, Durim Morina, Michael S. Bernstein

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

2018

Shared Autonomy for an Interactive AI System.

Sharon Zhou, Tong Mu, Karan Goel, Michael S. Bernstein, Emma Brunskill

Proceedings of the 31st Annual ACM Symposium on User Interface Software and Technology Adjunct Proceedings, 2018

In Search of the Dream Team: Temporally Constrained Multi-Armed Bandits for Identifying Effective Team Structures.

Sharon Zhou, Melissa A. Valentine, Michael S. Bernstein

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 2018

2017

Prototype Tasks: Improving Crowdsourcing Results through Rapid, Iterative Task Design.

Snehalkumar (Neil) S. Gaikwad, Nalin Chhibber, Vibhor Sehgal, Alipta Ballav, Catherine A. Mullings, Ahmed Nasser, Angela Richmond-Fuller, Aaron Gilbee, Dilrukshi Gamage, Mark E. Whiting, Sharon Zhou, Sekandar Matin, Senadhipathige S. Niranga, Shirish Goyal, Dinesh Majeti, Preethi Srinivas, Adam Ginzberg, Kamila Mananova, Karolina R. Ziulkoski, Jeff Regino, Tejas Sarma, Akshansh Sinha, Abhratanu Paul, Christopher Diemert, Mahesh Murag, William Dai, Manoj Pandey, Rajan Vaish, Michael S. Bernstein

CoRR, 2017

The Daemo Crowdsourcing Marketplace.

Snehalkumar (Neil) S. Gaikwad, Mark E. Whiting, Dilrukshi Gamage, Catherine A. Mullings, Dinesh Majeti, Shirish Goyal, Aaron Gilbee, Nalin Chhibber, Adam Ginzberg, Angela Richmond-Fuller, Sekandar Matin, Vibhor Sehgal, Tejas Seshadri Sarma, Ahmed Nasser, Alipta Ballav, Jeff Regino, Sharon Zhou, Kamila Mananova, Preethi Srinivas, Karolina R. Ziulkoski, Dinesh Dhakal, Alexander Stolzoff, Senadhipathige S. Niranga, Mohamed Hashim Salih, Akshansh Sinha, Rajan Vaish, Michael S. Bernstein

Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, 2017

2016

Boomerang: Rebounding the Consequences of Reputation Feedback on Crowdsourcing Platforms.

Snehalkumar (Neil) S. Gaikwad, Durim Morina, Adam Ginzberg, Catherine A. Mullings, Shirish Goyal, Dilrukshi Gamage, Christopher Diemert, Mathias Burton, Sharon Zhou, Mark E. Whiting, Karolina R. Ziulkoski, Alipta Ballav, Aaron Gilbee, Senadhipathige S. Niranga, Vibhor Sehgal, Jasmine Lin, Leonardy Kristianto, Angela Richmond-Fuller, Jeff Regino, Nalin Chhibber, Dinesh Majeti, Sachin Sharma, Kamila Mananova, Dinesh Dhakal, William Dai, Victoria Purynova, Samarth Sandeep, Varshine Chandrakanthan, Tejas Sarma, Sekandar Matin, Ahmed Nasser, Rohit Nistala, Alexander Stolzoff, Kristy Milland, Vinayak Mathur, Rajan Vaish, Michael S. Bernstein

Proceedings of the 29th Annual Symposium on User Interface Software and Technology, 2016

Ingenium: Engaging Novice Students with Latin Grammar.

Sharon Zhou, Ivy J. Livingston, Mark Schiefsky, Stuart M. Shieber, Krzysztof Z. Gajos

Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, 2016