Search Results for author: Zichen Wang

Found 38 papers, 16 papers with code

Toward Rich Video Human-Motion2D Generation

no code implementations17 Jun 2025 Ruihao Xi, Xuekuan Wang, Yongcheng Li, Shuhua Li, Zichen Wang, Yiwei Wang, Feng Wei, Cairong Zhao

Generating realistic and controllable human motions, particularly those involving rich multi-character interactions, remains a significant challenge due to data scarcity and the complexities of modeling inter-personal dynamics.

VideoPDE: Unified Generative PDE Solving via Video Inpainting Diffusion Models

no code implementations16 Jun 2025 Edward Li, Zichen Wang, Jiahe Huang, Jeong Joon Park

We present a unified framework for solving partial differential equations (PDEs) using video-inpainting diffusion transformer models.

Computational Efficiency Missing Values +1

Zero-shot Medical Event Prediction Using a Generative Pre-trained Transformer on Electronic Health Records

no code implementations7 Mar 2025 Ekaterina Redekop, Zichen Wang, Rushikesh Kulkarni, Mara Pleasure, Aaron Chin, Hamid Reza Hassanzadeh, Brian L. Hill, Melika Emami, William Speier, Corey W. Arnold

This study presents the first comprehensive analysis of zero-shot forecasting with GPT-based foundational models in EHRs, introducing a novel pipeline that formulates medical concept prediction as a generative modeling task.

Diagnostic

Protein Structure Tokenization: Benchmarking and New Recipe

1 code implementation28 Feb 2025 Xinyu Yuan, Zichen Wang, Marcus Collins, Huzefa Rangwala

Recent years have witnessed a surge in the development of protein structural tokenization methods, which chunk protein 3D structures into discrete or continuous representations.

Benchmarking Language Modeling +1

AffinityFlow: Guided Flows for Antibody Affinity Maturation

no code implementations14 Feb 2025 Can Chen, Karla-Luise Herpoldt, Chenchao Zhao, Zichen Wang, Marcus Collins, Shang Shang, Ron Benson

Antibodies are widely used as therapeutics, but their development requires costly affinity maturation, involving iterative mutations to enhance binding affinity. This paper explores a sequence-only scenario for affinity maturation, using solely antibody and antigen sequences.

C2F-TP: A Coarse-to-Fine Denoising Framework for Uncertainty-Aware Trajectory Prediction

1 code implementation17 Dec 2024 Zichen Wang, Hao Miao, Senzhang Wang, Renzhi Wang, Jianxin Wang, Jian Zhang

Accurately predicting the trajectory of vehicles is critically important for ensuring safety and reliability in autonomous driving.

Autonomous Driving Denoising +2

Online Experimental Design With Estimation-Regret Trade-off Under Network Interference

no code implementations4 Dec 2024 Zhiheng Zhang, Zichen Wang

Network interference has attracted significant attention in the field of causal inference, encapsulating various sociological behaviors where the treatment assigned to one individual within a network may affect the outcomes of others, such as their neighbors.

Causal Inference Experimental Design

Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers

1 code implementation29 Oct 2024 Yingheng Wang, Zichen Wang, Gil Sadeh, Luca Zancato, Alessandro Achille, George Karypis, Huzefa Rangwala

Self-supervised training of language models (LMs) has seen great success for protein sequences in learning meaningful representations and for generative drug design.

Drug Design Language Modeling +5

Pushing the Limits of All-Atom Geometric Graph Neural Networks: Pre-Training, Scaling and Zero-Shot Transfer

no code implementations29 Oct 2024 Zihan Pengmei, Zhengyuan Shen, Zichen Wang, Marcus Collins, Huzefa Rangwala

In this work, we explored the possibility of using pre-trained Geom-GNNs as transferable and highly effective geometric descriptors for improved generalization.

All Drug Discovery +1

Retrieval Augmented Diffusion Model for Structure-informed Antibody Design and Optimization

no code implementations19 Oct 2024 Zichen Wang, Yaokun Ji, Jianing Tian, Shuangjia Zheng

Our method leverages a set of structural homologous motifs that align with query structural constraints to guide the generative model in inversely optimizing antibodies according to desired design criteria.

Denoising Model Optimization +1

XNet v2: Fewer Limitations, Better Results and Greater Universality

1 code implementation2 Sep 2024 Yanfeng Zhou, Lingrui Li, Zichen Wang, Guole Liu, Ziwen Liu, Ge Yang

So far, however, XNet still faces the limitations, including performance degradation when images lack high-frequency (HF) information, underutilization of raw images and insufficient fusion.

DiffusionPDE: Generative PDE-Solving Under Partial Observation

1 code implementation25 Jun 2024 Jiahe Huang, Guandao Yang, Zichen Wang, Jeong Joon Park

We introduce a general framework for solving partial differential equations (PDEs) using generative diffusion models.

GraphStorm: all-in-one graph machine learning framework for industry applications

1 code implementation10 Jun 2024 Da Zheng, Xiang Song, Qi Zhu, Jian Zhang, Theodore Vasiloudis, Runjie Ma, Houyu Zhang, Zichen Wang, Soji Adeshina, Israt Nisa, Alejandro Mottini, Qingjun Cui, Huzefa Rangwala, Belinda Zeng, Christos Faloutsos, George Karypis

GraphStorm has the following desirable properties: (a) Easy to use: it can perform graph construction and model training and inference with just a single command; (b) Expert-friendly: GraphStorm contains many advanced GML modeling techniques to handle complex graph data and improve model performance; (c) Scalable: every component in GraphStorm can operate on graphs with billions of nodes and can scale model training and inference to different hardware without changing any code.

All graph construction

A Simple Approach to Differentiable Rendering of SDFs

no code implementations14 May 2024 Zichen Wang, Xi Deng, Ziyi Zhang, Wenzel Jakob, Steve Marschner

We present a simple algorithm for differentiable rendering of surfaces represented by Signed Distance Fields (SDF), which makes it easy to integrate rendering into gradient-based optimization pipelines.

Inverse Rendering

Fine-Grained Prototypes Distillation for Few-Shot Object Detection

1 code implementation15 Jan 2024 Zichen Wang, Bo Yang, Haonan Yue, Zhenghao Ma

However, the class-level prototypes are difficult to precisely generate, and they also lack detailed information, leading to instability in performance. New methods are required to capture the distinctive local context for more robust novel object detection.

Few-Shot Object Detection Meta-Learning +3

Accurate Differential Operators for Hybrid Neural Fields

1 code implementation CVPR 2025 Aditya Chetan, Guandao Yang, Zichen Wang, Steve Marschner, Bharath Hariharan

Yet in many applications like rendering and simulation, hybrid neural fields can cause noticeable and unreasonable artifacts.

Pure Exploration in Asynchronous Federated Bandits

no code implementations17 Oct 2023 Zichen Wang, Chuanhao Li, Chenyu Song, Lianghui Wang, Quanquan Gu, Huazheng Wang

We study the federated pure exploration problem of multi-armed bandits and linear bandits, where $M$ agents cooperatively identify the best arm via communicating with the central server.

Multi-Armed Bandits

BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs

1 code implementation5 Oct 2023 Zifeng Wang, Zichen Wang, Balasubramaniam Srinivasan, Vassilis N. Ioannidis, Huzefa Rangwala, Rishita Anubhai

Foundation models (FMs) are able to leverage large volumes of unlabeled data to demonstrate superior performance across a wide range of tasks.

Cross-Modal Retrieval Domain Generalization +3

Integration of Graph Neural Network and Neural-ODEs for Tumor Dynamic Prediction

no code implementations2 Oct 2023 Omid Bazgir, Zichen Wang, Ji Won Park, Marc Hafner, James Lu

Additionally, we show that the graph encoder is able to effectively utilize multimodal data to enhance tumor predictions.

Graph Neural Network

Graph Neural Prompting with Large Language Models

1 code implementation27 Sep 2023 Yijun Tian, Huan Song, Zichen Wang, Haozhu Wang, Ziqing Hu, Fang Wang, Nitesh V. Chawla, Panpan Xu

While existing work has explored utilizing knowledge graphs (KGs) to enhance language modeling via joint training and customized model architectures, applying this to LLMs is problematic owing to their large number of parameters and high computational cost.

Graph Neural Network Knowledge Graphs +5

Understanding Divergent Framing of the Supreme Court Controversies: Social Media vs. News Outlets

no code implementations18 Sep 2023 Jinsheng Pan, Zichen Wang, Weihong Qi, Hanjia Lyu, Jiebo Luo

Understanding the framing of political issues is of paramount importance as it significantly shapes how individuals perceive, interpret, and engage with these matters.

Decision Making

Bias or Diversity? Unraveling Fine-Grained Thematic Discrepancy in U.S. News Headlines

no code implementations28 Mar 2023 Jinsheng Pan, Weihong Qi, Zichen Wang, Hanjia Lyu, Jiebo Luo

There is a broad consensus that news media outlets incorporate ideological biases in their news articles.

Articles Diversity

Computational Assessment of Hyperpartisanship in News Titles

1 code implementation16 Jan 2023 Hanjia Lyu, Jinsheng Pan, Zichen Wang, Jiebo Luo

We first adopt a human-guided machine learning framework to develop a new dataset for hyperpartisan news title detection with 2, 200 manually labeled and 1. 8 million machine-labeled titles that were posted from 2014 to the present by nine representative media organizations across three media bias groups - Left, Central, and Right in an active learning manner.

Active Learning Language Modelling

Training self-supervised peptide sequence models on artificially chopped proteins

no code implementations9 Nov 2022 Gil Sadeh, Zichen Wang, Jasleen Grewal, Huzefa Rangwala, Layne Price

In this paper, we propose a new peptide data augmentation scheme, where we train peptide language models on artificially constructed peptides that are small contiguous subsets of longer, wild-type proteins; we refer to the training peptides as "chopped proteins".

Data Augmentation Language Modeling +3

Variational Causal Inference

2 code implementations13 Sep 2022 Yulun Wu, Layne C. Price, Zichen Wang, Vassilis N. Ioannidis, Robert A. Barton, George Karypis

Estimating an individual's potential outcomes under counterfactual treatments is a challenging task for traditional causal inference and supervised learning approaches when the outcome is high-dimensional (e. g. gene expressions, impulse responses, human faces) and covariates are relatively limited.

Causal Inference counterfactual

Graph Convolutional Networks for Multi-modality Medical Imaging: Methods, Architectures, and Clinical Applications

no code implementations17 Feb 2022 Kexin Ding, Mu Zhou, Zichen Wang, Qiao Liu, Corey W. Arnold, Shaoting Zhang, Dimitri N. Metaxas

Image-based characterization and disease understanding involve integrative analysis of morphological, spatial, and topological information across biological scales.

Medical Image Analysis

Toward heterogeneous information fusion: bipartite graph convolutional networks for in silico drug repurposing

1 code implementation Bioinformatics, Volume 36, Issue Supplement_1 2020 Zichen Wang, Mu Zhou, Corey Arnold

Unlike conventional graph convolution networks always assuming the same node attributes in a global graph, our approach models interdomain information fusion with bipartite graph convolution operation.

Drug Discovery

Cannot find the paper you are looking for? You can Submit a new open access paper.