Jiacheng Zhu | DeepAI

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∙ 07/30/2023

Interactive Car-Following: Matters but NOT Always

Following a leading vehicle is a daily but challenging task because it r...

0 Chengyuan Zhang, et al. ∙

∙ 06/15/2023

Datasets and Benchmarks for Offline Safe Reinforcement Learning

This paper presents a comprehensive benchmarking suite tailored to offli...

0 Zuxin Liu, et al. ∙

∙ 06/07/2023

MultiSum: A Dataset for Multimodal Summarization and Thumbnail Generation of Videos

Multimodal summarization with multimodal output (MSMO) has emerged as a ...

0 Jielin Qiu, et al. ∙

∙ 04/16/2023

Multimodal Representation Learning of Cardiovascular Magnetic Resonance Imaging

Self-supervised learning is crucial for clinical imaging applications, g...

0 Jielin Qiu, et al. ∙

∙ 03/09/2023

GOATS: Goal Sampling Adaptation for Scooping with Curriculum Reinforcement Learning

In this work, we first formulate the problem of goal-conditioned robotic...

3 Yaru Niu, et al. ∙

∙ 02/04/2023

Interpolation for Robust Learning: Data Augmentation on Geodesics

We propose to study and promote the robustness of a model as per its per...

0 Jiacheng Zhu, et al. ∙

∙ 01/21/2023

Transfer Knowledge from Natural Language to Electrocardiography: Can We Detect Cardiovascular Disease Through Language Models?

Recent advancements in Large Language Models (LLMs) have drawn increasin...

13 Jielin Qiu, et al. ∙

∙ 10/18/2022

Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation

Curriculum Reinforcement Learning (CRL) aims to create a sequence of tas...

21 Peide Huang, et al. ∙

∙ 10/10/2022

Semantics-Consistent Cross-domain Summarization via Optimal Transport Alignment

Multimedia summarization with multimodal output (MSMO) is a recently exp...

9 Jielin Qiu, et al. ∙

∙ 10/04/2022

Robustness Certification of Visual Perception Models via Camera Motion Smoothing

A vast literature shows that the learning-based visual perception model ...

6 Hanjiang Hu, et al. ∙

∙ 08/10/2022

An Empirical Exploration of Cross-domain Alignment between Language and Electroencephalogram

Electroencephalography (EEG) and language have been widely explored inde...

19 William Han, et al. ∙

∙ 08/02/2022

GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Electrocardiogram Prediction

There has been an increased interest in applying deep neural networks to...

0 Jiacheng Zhu, et al. ∙

∙ 04/07/2022

MHMS: Multimodal Hierarchical Multimedia Summarization

Multimedia summarization with multimodal output can play an essential ro...

0 Jielin Qiu, et al. ∙

∙ 03/19/2022

PhysioMTL: Personalizing Physiological Patterns using Optimal Transport Multi-Task Regression

Heart rate variability (HRV) is a practical and noninvasive measure of a...

0 Jiacheng Zhu, et al. ∙

∙ 01/25/2022

Optimal Transport based Data Augmentation for Heart Disease Diagnosis and Prediction

In this paper, we focus on a new method of data augmentation to solve th...

1 Jielin Qiu, et al. ∙

∙ 06/19/2021

Accelerated Policy Evaluation: Learning Adversarial Environments with Adaptive Importance Sampling

The evaluation of rare but high-stakes events remains one of the main di...

0 Mengdi Xu, et al. ∙

∙ 02/07/2021

Functional Optimal Transport: Mapping Estimation and Domain Adaptation for Functional data

Optimal transport (OT) has generated much recent interest by its capabil...

0 Jiacheng Zhu, et al. ∙

∙ 01/02/2021

Context-Aware Safe Reinforcement Learning for Non-Stationary Environments

Safety is a critical concern when deploying reinforcement learning agent...

0 Baiming Chen, et al. ∙

∙ 06/19/2020

Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes

Continuously learning to solve unseen tasks with limited experience has ...

0 Mengdi Xu, et al. ∙

∙ 06/18/2020

Robust Unsupervised Learning of Temporal Dynamic Interactions

Robust representation learning of temporal dynamic interactions is an im...

0 Aritra Guha, et al. ∙

∙ 03/02/2020

Spatiotemporal Learning of Multivehicle Interaction Patterns in Lane-Change Scenarios

Interpretation of common-yet-challenging interaction scenarios can benef...

0 Chengyuan Zhang, et al. ∙

∙ 10/17/2019

Probabilistic Trajectory Prediction for Autonomous Vehicles with Attentive Recurrent Neural Process

Predicting surrounding vehicle behaviors are critical to autonomous vehi...

0 Jiacheng Zhu, et al. ∙

∙ 10/17/2019

Recurrent Attentive Neural Process for Sequential Data

Neural processes (NPs) learn stochastic processes and predict the distri...

0 Shenghao Qin, et al. ∙

∙ 07/17/2019

A General Framework of Learning Multi-Vehicle Interaction Patterns from Videos

Semantic learning and understanding of multi-vehicle interaction pattern...

9 Chengyuan Zhang, et al. ∙

∙ 06/25/2019

Modeling Multi-Vehicle Interaction Scenarios Using Gaussian Random Field

Autonomous vehicles (AV) are expected to navigate in complex traffic sce...

0 Yaohui Guo, et al. ∙

∙ 04/23/2019

Estimating Risk Levels of Driving Scenarios through Analysis of Driving Styles for Autonomous Vehicles

In order to operate safely on the road, autonomous vehicles need not onl...

0 Songlin Xu, et al. ∙

∙ 05/13/2018

A Tempt to Unify Heterogeneous Driving Databases using Traffic Primitives

A multitude of publicly-available driving datasets and data platforms ha...

0 Jiacheng Zhu, et al. ∙

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