
Traffic Forecasting using VehicletoVehicle Communication
We take the first step in using vehicletovehicle (V2V) communication t...
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Generator Surgery for Compressed Sensing
Image recovery from compressive measurements requires a signal prior for...
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MetaLearning Dynamics Forecasting Using Task Inference
Current deep learning models for dynamics forecasting struggle with gene...
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DeepGLEAM: a hybrid mechanistic and deep learning model for COVID19 forecasting
We introduce DeepGLEAM, a hybrid model for COVID19 forecasting. DeepGLE...
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Bridging Physicsbased and Datadriven modeling for Learning Dynamical Systems
How can we learn a dynamical system to make forecasts, when some variabl...
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Trajectory Prediction using Equivariant Continuous Convolution
Trajectory prediction is a critical part of many AI applications, for ex...
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Deep Imitation Learning for Bimanual Robotic Manipulation
We present a deep imitation learning framework for robotic bimanual mani...
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Learning Disentangled Representations of Video with Missing Data
Missing data poses significant challenges while learning representations...
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Finding Patient Zero: Learning Contagion Source with Graph Neural Networks
Locating the source of an epidemic, or patient zero (P0), can provide cr...
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Aortic Pressure Forecasting with Deep Sequence Learning
Mean aortic pressure is a major determinant of perfusion in all organ sy...
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Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis
Efficient and interpretable spatial analysis is crucial in many fields s...
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Incorporating Symmetry into Deep Dynamics Models for Improved Generalization
Training machine learning models that can learn complex spatiotemporal d...
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Towards Physicsinformed Deep Learning for Turbulent Flow Prediction
While deep learning has shown tremendous success in a wide range of doma...
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Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology
To deepen our understanding of graph neural networks, we investigate the...
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NAOMI: NonAutoregressive Multiresolution Sequence Imputation
Missing value imputation is a fundamental problem in modeling spatiotemp...
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Neural Lander: Stable Drone Landing Control using Learned Dynamics
Precise trajectory control near ground is difficult for multirotor dron...
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Learning Tensor Latent Features
We study the problem of learning latent feature models (LFMs) for tensor...
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Multiresolution Tensor Learning for LargeScale Spatial Data
Highdimensional tensor models are notoriously computationally expensive...
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Tensor Regression Meets Gaussian Processes
Lowrank tensor regression, a new model class that learns highorder cor...
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Diffusion Convolutional Recurrent Neural Network: DataDriven Traffic Forecasting
Spatiotemporal forecasting has various applications in neuroscience, cli...
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Socratic Learning: Augmenting Generative Models to Incorporate Latent Subsets in Training Data
A challenge in training discriminative models like neural networks is ob...
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Rose Yu
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