Rose Yu

Affiliations:
  • University of California, San Diego, CA, USA
  • Northeastern University, MA, USA (former)
  • Caltech, CA, USA (former)
  • University of Southern California, CA, USA (former)


According to our database1, Rose Yu authored at least 43 papers between 2011 and 2021.

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Bibliography

2021
AI-Bind: Improving Binding Predictions for Novel Protein Targets and Ligands.
CoRR, 2021

Neural Point Process for Learning Spatiotemporal Event Dynamics.
CoRR, 2021

Automatic Symmetry Discovery with Lie Algebra Convolutional Network.
CoRR, 2021

Accelerating Stochastic Simulation with Interactive Neural Processes.
CoRR, 2021

Generator Surgery for Compressed Sensing.
CoRR, 2021

Meta-Learning Dynamics Forecasting Using Task Inference.
CoRR, 2021

DeepGLEAM: a hybrid mechanistic and deep learning model for COVID-19 forecasting.
CoRR, 2021

Traffic Forecasting using Vehicle-to-Vehicle Communication.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Physics-Guided AI for Large-Scale Spatiotemporal Data.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Quantifying Uncertainty in Deep Spatiotemporal Forecasting.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

The 4th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK 4.0 @ KDD2021).
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Incorporating Symmetry into Deep Dynamics Models for Improved Generalization.
Proceedings of the 9th International Conference on Learning Representations, 2021

Trajectory Prediction using Equivariant Continuous Convolution.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Dynamic Relational Inference in Multi-Agent Trajectories.
CoRR, 2020

Learning Disentangled Representations of Video with Missing Data.
CoRR, 2020

Finding Patient Zero: Learning Contagion Source with Graph Neural Networks.
CoRR, 2020

Aortic Pressure Forecasting with Deep Sequence Learning.
CoRR, 2020

Learning Disentangled Representations of Videos with Missing Data.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Deep Imitation Learning for Bimanual Robotic Manipulation.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Towards Physics-informed Deep Learning for Turbulent Flow Prediction.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis.
Proceedings of the 37th International Conference on Machine Learning, 2020

Aortic Pressure Forecasting With Deep Learning.
Proceedings of the Computing in Cardiology, 2020

2019
NAOMI: Non-Autoregressive Multiresolution Sequence Imputation.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Neural Lander: Stable Drone Landing Control Using Learned Dynamics.
Proceedings of the International Conference on Robotics and Automation, 2019

2018
Learning Tensor Latent Features.
CoRR, 2018

Multi-resolution Tensor Learning for Large-Scale Spatial Data.
CoRR, 2018

Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting.
Proceedings of the 6th International Conference on Learning Representations, 2018

Tensor Regression Meets Gaussian Processes.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Spatiotemporal Analysis of Social Media Data.
Proceedings of the Encyclopedia of GIS., 2017

Long-term Forecasting using Tensor-Train RNNs.
CoRR, 2017

Graph Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting.
CoRR, 2017

Deep Learning: A Generic Approach for Extreme Condition Traffic Forecasting.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

2016
A Survey on Social Media Anomaly Detection.
SIGKDD Explor., 2016

Socratic Learning.
CoRR, 2016

Geographic Segmentation via Latent Poisson Factor Model.
Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 2016

Latent Space Model for Road Networks to Predict Time-Varying Traffic.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Learning from Multiway Data: Simple and Efficient Tensor Regression.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
GLAD: Group Anomaly Detection in Social Media Analysis.
ACM Trans. Knowl. Discov. Data, 2015

Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Fast Multivariate Spatio-temporal Analysis via Low Rank Tensor Learning.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2011
A Feasible Nonconvex Relaxation Approach to Feature Selection.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011


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