b'Zhen Zhang'

research

∙ 09/15/2023

RADE: Reference-Assisted Dialogue Evaluation for Open-Domain Dialogue

Evaluating open-domain dialogue systems is challenging for reasons such ...

0 Zhengliang Shi, et al. ∙

research

∙ 09/15/2023

Oobleck: Resilient Distributed Training of Large Models Using Pipeline Templates

Oobleck enables resilient distributed training of large DNN models with ...

0 Insu Jang, et al. ∙

research

∙ 08/30/2023

AI-powered Fraud Detection in Decentralized Finance: A Project Life Cycle Perspective

In recent years, blockchain technology has introduced decentralized fina...

0 Bingqiao Luo, et al. ∙

research

∙ 08/30/2023

Depth analysis of battery performance based on a data-driven approach

Capacity attenuation is one of the most intractable issues in the curren...

0 Zhen Zhang, et al. ∙

research

∙ 08/02/2023

Factor Graph Neural Networks

In recent years, we have witnessed a surge of Graph Neural Networks (GNN...

0 Zhen Zhang, et al. ∙

research

∙ 07/16/2023

Discovering a reaction-diffusion model for Alzheimer's disease by combining PINNs with symbolic regression

Misfolded tau proteins play a critical role in the progression and patho...

0 Zhen Zhang, et al. ∙

research

∙ 07/05/2023

OpenDelta: A Plug-and-play Library for Parameter-efficient Adaptation of Pre-trained Models

The scale of large pre-trained models (PTMs) poses significant challenge...

0 Shengding Hu, et al. ∙

research

∙ 06/05/2023

Uncertainty in Natural Language Processing: Sources, Quantification, and Applications

As a main field of artificial intelligence, natural language processing ...

0 Mengting Hu, et al. ∙

research

∙ 06/01/2023

Uncertainty-Aware Unlikelihood Learning Improves Generative Aspect Sentiment Quad Prediction

Recently, aspect sentiment quad prediction has received widespread atten...

0 Mengting Hu, et al. ∙

research

∙ 05/29/2023

E-NER: Evidential Deep Learning for Trustworthy Named Entity Recognition

Most named entity recognition (NER) systems focus on improving model per...

0 Zhen Zhang, et al. ∙

research

∙ 05/02/2023

Parameter-Efficient Cross-lingual Transfer of Vision and Language Models via Translation-based Alignment

Pre-trained vision and language models such as CLIP have witnessed remar...

0 Zhen Zhang, et al. ∙

research

∙ 04/17/2023

Tool Learning with Foundation Models

Humans possess an extraordinary ability to create and utilize tools, all...

1 Yujia Qin, et al. ∙

research

∙ 03/29/2023

BERT4ETH: A Pre-trained Transformer for Ethereum Fraud Detection

As various forms of fraud proliferate on Ethereum, it is imperative to s...

0 Sihao Hu, et al. ∙

research

∙ 03/25/2023

Multi-pooling 3D Convolutional Neural Network for fMRI Classification of Visual Brain States

Neural decoding of visual object classification via functional magnetic ...

0 Zhen Zhang, et al. ∙

research

∙ 02/16/2023

Decoupled Model Schedule for Deep Learning Training

Recent years have seen an increase in the development of large deep lear...

0 Hongzheng Chen, et al. ∙

research

∙ 09/17/2022

A Diffuse-Domain Based Numerical Method for a Chemotaxis-Fluid Model

In this paper, we consider a coupled chemotaxis-fluid system that models...

0 Chenxi Wang, et al. ∙

research

∙ 07/11/2022

Counterexample Generation for Infinite-State Chemical Reaction Networks

Counterexample generation is an indispensable part of model checking pro...

0 Mohammad Ahmadi, et al. ∙

research

∙ 06/15/2022

Sparse Structure Search for Parameter-Efficient Tuning

Adapting large pre-trained models (PTMs) through fine-tuning imposes pro...

11 Shengding Hu, et al. ∙

research

∙ 05/25/2022

NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results

This paper reviews the challenge on constrained high dynamic range (HDR)...

0 Eduardo Pérez-Pellitero, et al. ∙

research

∙ 05/23/2022

MolMiner: You only look once for chemical structure recognition

Molecular structures are always depicted as 2D printed form in scientifi...

0 Youjun Xu, et al. ∙

research

∙ 04/30/2022

MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud

Existing general purpose frameworks for gigantic model training, i.e., m...

0 Zhen Zhang, et al. ∙

research

∙ 04/21/2022

Sequence-Based Target Coin Prediction for Cryptocurrency Pump-and-Dump

As the pump-and-dump schemes (P Ds) proliferate in the cryptocurrency ...

0 Sihao Hu, et al. ∙

research

∙ 02/03/2022

Systems Biology: Identifiability analysis and parameter identification via systems-biology informed neural networks

The dynamics of systems biological processes are usually modeled by a sy...

7 Mitchell Daneker, et al. ∙

research

∙ 01/14/2022

SympOCnet: Solving optimal control problems with applications to high-dimensional multi-agent path planning problems

Solving high-dimensional optimal control problems in real-time is an imp...

7 Tingwei Meng, et al. ∙

research

∙ 01/10/2022

MyoPS: A Benchmark of Myocardial Pathology Segmentation Combining Three-Sequence Cardiac Magnetic Resonance Images

Assessment of myocardial viability is essential in diagnosis and treatme...

8 Lei Li, et al. ∙

research

∙ 09/08/2021

Learning Local-Global Contextual Adaptation for Fully End-to-End Bottom-Up Human Pose Estimation

This paper presents a method of learning Local-GlObal Contextual Adaptat...

10 Nan Xue, et al. ∙

research

∙ 08/31/2021

GFINNs: GENERIC Formalism Informed Neural Networks for Deterministic and Stochastic Dynamical Systems

We propose the GENERIC formalism informed neural networks (GFINNs) that ...

6 Zhen Zhang, et al. ∙

research

∙ 07/30/2021

Adaptive Optimizers with Sparse Group Lasso for Neural Networks in CTR Prediction

We develop a novel framework that adds the regularizers of the sparse gr...

0 Yun Yue, et al. ∙

research

∙ 07/14/2021

Semi-Supervised Hypothesis Transfer for Source-Free Domain Adaptation

Domain Adaptation has been widely used to deal with the distribution shi...

0 Ning Ma, et al. ∙

research

∙ 07/14/2021

Uncertainty-Guided Mixup for Semi-Supervised Domain Adaptation without Source Data

Present domain adaptation methods usually perform explicit representatio...

0 Ning Ma, et al. ∙

research

∙ 06/09/2021

Ultra High Dimensional Change Point Detection

Structural breaks have been commonly seen in applications. Specifically ...

0 Xin Liu, et al. ∙

research

∙ 04/06/2021

A Thermodynamically Consistent Model and Its Conservative Numerical Approximation for Moving Contact Lines with Soluble Surfactants

We derive a continuum sharp-interface model for moving contact lines wit...

0 Quan Zhao, et al. ∙

research

∙ 03/22/2021

Automatic Pulmonary Artery and Vein Separation Algorithm Based on Multitask Classification Network and Topology Reconstruction in Chest CT Images

With the development of medical computer-aided diagnostic systems, pulmo...

0 Lin Pan, et al. ∙

research

∙ 12/23/2020

Market Impact in Trader-Agents: Adding Multi-Level Order-Flow Imbalance-Sensitivity to Automated Trading Systems

Financial markets populated by human traders often exhibit "market impac...

0 Zhen Zhang, et al. ∙

research

∙ 12/05/2020

Learning Poisson systems and trajectories of autonomous systems via Poisson neural networks

We propose the Poisson neural networks (PNNs) to learn Poisson systems a...

12 Pengzhan Jin, et al. ∙

research

∙ 11/24/2020

Cyclic Label Propagation for Graph Semi-supervised Learning

Graph neural networks (GNNs) have emerged as effective approaches for gr...

0 Zhao Li, et al. ∙

research

∙ 11/13/2020

Deep Reinforcement Learning of Transition States

Combining reinforcement learning (RL) and molecular dynamics (MD) simula...

41 Jun Zhang, et al. ∙

research

∙ 11/01/2020

CL-MAPF: Multi-Agent Path Finding for Car-Like Robots with Kinematic and Spatiotemporal Constraints

Multi-Agent Path Finding has been widely studied in the past few years d...

0 Licheng Wen, et al. ∙

research

∙ 10/29/2020

Brain Tumor Segmentation Network Using Attention-based Fusion and Spatial Relationship Constraint

Delineating the brain tumor from magnetic resonance (MR) images is criti...

0 Chenyu Liu, et al. ∙

research

∙ 08/13/2020

Multi-Modality Pathology Segmentation Framework: Application to Cardiac Magnetic Resonance Images

Multi-sequence of cardiac magnetic resonance (CMR) images can provide co...

0 Zhen Zhang, et al. ∙

research

∙ 08/04/2020

Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence

Distributed linguistic representations are powerful tools for modelling ...

0 Yuzhu Wu, et al. ∙

research

∙ 06/17/2020

Is Network the Bottleneck of Distributed Training?

Recently there has been a surge of research on improving the communicati...

0 Zhen Zhang, et al. ∙

research

∙ 06/07/2020

MIM: A deep mixed residual method for solving high-order partial differential equations

In recent years, a significant amount of attention has been paid to solv...

0 Liyao Lyu, et al. ∙

research

∙ 04/25/2020

A Perspective on Deep Learning for Molecular Modeling and Simulations

Deep learning is transforming many areas in science, and it has great po...

0 Jun Zhang, et al. ∙

research

∙ 03/18/2020

Few-Shot Graph Classification with Model Agnostic Meta-Learning

Graph classification aims to perform accurate information extraction and...

0 Ning Ma, et al. ∙

research

∙ 02/29/2020

Multiplicative Gaussian Particle Filter

We propose a new sampling-based approach for approximate inference in fi...

0 Xuan Su, et al. ∙

research

∙ 11/25/2019

KerGM: Kernelized Graph Matching

Graph matching plays a central role in such fields as computer vision, p...

0 Zhen Zhang, et al. ∙

research

∙ 11/25/2019

Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding

Graph kernels are widely used for measuring the similarity between graph...

0 Lingfei Wu, et al. ∙

research

∙ 11/22/2019

Visual Relationship Detection with Low Rank Non-Negative Tensor Decomposition

We address the problem of Visual Relationship Detection (VRD) which aims...

18 Mohammed Haroon Dupty, et al. ∙

research

∙ 11/14/2019

Hierarchical Graph Pooling with Structure Learning

Graph Neural Networks (GNNs), which generalize deep neural networks to g...

0 Zhen Zhang, et al. ∙

Zhen Zhang

Featured Co-authors