Haohan Wang
Orcid: 0000-0002-1826-4069
According to our database1,
Haohan Wang
authored at least 114 papers
between 2013 and 2024.
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Bibliography
2024
IEEE Trans. Pattern Anal. Mach. Intell., June, 2024
Choosing Wisely and Learning Deeply: Selective Cross-Modality Distillation via CLIP for Domain Generalization.
Trans. Mach. Learn. Res., 2024
SAR Incremental Automatic Target Recognition Based on Mutual Information Maximization.
IEEE Geosci. Remote. Sens. Lett., 2024
CoRR, 2024
DS-ViT: Dual-Stream Vision Transformer for Cross-Task Distillation in Alzheimer's Early Diagnosis.
CoRR, 2024
A Quantitative Approach for Evaluating Disease Focus and Interpretability of Deep Learning Models for Alzheimer's Disease Classification.
CoRR, 2024
Quantitative Evaluation of the Saliency Map for Alzheimer's Disease Classifier with Anatomical Segmentation.
CoRR, 2024
JailbreakZoo: Survey, Landscapes, and Horizons in Jailbreaking Large Language and Vision-Language Models.
CoRR, 2024
GenoTEX: A Benchmark for Evaluating LLM-Based Exploration of Gene Expression Data in Alignment with Bioinformaticians.
CoRR, 2024
Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas.
CoRR, 2024
From Tissue Plane to Organ World: A Benchmark Dataset for Multimodal Biomedical Image Registration using Deep Co-Attention Networks.
CoRR, 2024
Jailbreaking Large Language Models Against Moderation Guardrails via Cipher Characters.
CoRR, 2024
The Devil is in the Edges: Monocular Depth Estimation with Edge-aware Consistency Fusion.
CoRR, 2024
CoRR, 2024
CoRR, 2024
Beyond Finite Data: Towards Data-free Out-of-distribution Generalization via Extrapolation.
CoRR, 2024
Toward a Team of AI-made Scientists for Scientific Discovery from Gene Expression Data.
CoRR, 2024
GUARD: Role-playing to Generate Natural-language Jailbreakings to Test Guideline Adherence of Large Language Models.
CoRR, 2024
Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks.
CoRR, 2024
MedTransformer: Accurate AD Diagnosis for 3D MRI Images through 2D Vision Transformers.
CoRR, 2024
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024
A Lightweight Network for Radar Specific Emitter Identification via Differential Constellation Figure.
Proceedings of the IGARSS 2024, 2024
Language Agent Tree Search Unifies Reasoning, Acting, and Planning in Language Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the IEEE International Conference on Communications Workshops, 2024
User Preferences for Icon Design Styles and Their Associations with Personality and Demographic.
Proceedings of the HCI International 2024 Posters, 2024
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
Proceedings of the Computer Vision - ECCV 2024, 2024
Proceedings of the Computer Vision - ECCV 2024, 2024
Proceedings of the Computer Vision - ECCV 2024, 2024
EditShield: Protecting Unauthorized Image Editing by Instruction-Guided Diffusion Models.
Proceedings of the Computer Vision - ECCV 2024, 2024
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024
2023
IEEE Trans. Artif. Intell., June, 2023
Generate E-commerce Product Background by Integrating Category Commonality and Personalized Style.
CoRR, 2023
Beyond Pixels: Exploring Human-Readable SVG Generation for Simple Images with Vision Language Models.
CoRR, 2023
CoRR, 2023
Towards Trustworthy and Aligned Machine Learning: A Data-centric Survey with Causality Perspectives.
CoRR, 2023
Leveraging Large Language Models for Scalable Vector Graphics-Driven Image Understanding.
CoRR, 2023
Efficiently Leveraging Multi-level User Intent for Session-based Recommendation via Atten-Mixer Network.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023
A Sentence Speaks a Thousand Images: Domain Generalization through Distilling CLIP with Language Guidance.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Proceedings of the 47th IEEE Annual Computers, Software, and Applications Conference, 2023
Toward Robust Diagnosis: A Contour Attention Preserving Adversarial Defense for COVID-19 Detection.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
J. Comput. Biol., 2022
A Principled Evaluation Protocol for Comparative Investigation of the Effectiveness of DNN Classification Models on Similar-but-non-identical Datasets.
CoRR, 2022
Robustar: Interactive Toolbox Supporting Precise Data Annotation for Robust Vision Learning.
CoRR, 2022
CoRR, 2022
The Two Dimensions of Worst-case Training and the Integrated Effect for Out-of-domain Generalization.
CoRR, 2022
Toward learning human-aligned cross-domain robust models by countering misaligned features.
Proceedings of the Uncertainty in Artificial Intelligence, 2022
Gene Set Priorization Guided by Regulatory Networks with p-values through Kernel Mixed Model.
Proceedings of the Research in Computational Molecular Biology, 2022
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022
Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
The Two Dimensions of Worst-case Training and Their Integrated Effect for Out-of-domain Generalization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
2021
J. Comput. Biol., May, 2021
Toward Learning Human-aligned Cross-domain Robust Models by Countering Misaligned Features.
CoRR, 2021
Coupled mixed model for joint genetic analysis of complex disorders with two independently collected data sets.
BMC Bioinform., 2021
Active learning to classify macromolecular structures in situ for less supervision in cryo-electron tomography.
Bioinform., 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
2020
Poly(A)-DG: A deep-learning-based domain generalization method to identify cross-species Poly(A) signal without prior knowledge from target species.
PLoS Comput. Biol., November, 2020
Squared 𝓁<sub>2</sub> Norm as Consistency Loss for Leveraging Augmented Data to Learn Robust and Invariant Representations.
CoRR, 2020
Proceedings of the Computer Vision - ECCV 2020, 2020
High-Frequency Component Helps Explain the Generalization of Convolutional Neural Networks.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
2019
IEEE Trans. Intell. Transp. Syst., 2019
Discovery of Critical Nodes in Road Networks Through Mining From Vehicle Trajectories.
IEEE Trans. Intell. Transp. Syst., 2019
High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks.
CoRR, 2019
Deep mixed model for marginal epistasis detection and population stratification correction in genome-wide association studies.
BMC Bioinform., 2019
Precision Lasso: accounting for correlations and linear dependencies in high-dimensional genomic data.
Bioinform., 2019
Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications.
Proceedings of the Biocomputing 2019: Proceedings of the Pacific Symposium, 2019
Automatic Human-like Mining and Constructing Reliable Genetic Association Database with Deep Reinforcement Learning.
Proceedings of the Biocomputing 2019: Proceedings of the Pacific Symposium, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the 7th International Conference on Learning Representations, 2019
Regularized Adversarial Training (RAT) for Robust Cellular Electron Cryo Tomograms Classification.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019
Graph-structured Sparse Mixed Models for Genetic Association with Confounding Factors Correction.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019
Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP, 2019
What if We Simply Swap the Two Text Fragments? A Straightforward yet Effective Way to Test the Robustness of Methods to Confounding Signals in Nature Language Inference Tasks.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
2018
IEEE Trans. Comput. Soc. Syst., 2018
CoRR, 2018
Proceedings of the Big Data - BigData 2018, 2018
Heterogeneous Hi-C Data Super-resolution with a Conditional Generative Adversarial Network.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018
2017
Extracting compact representation of knowledge from gene expression data for protein-protein interaction.
Int. J. Data Min. Bioinform., 2017
A Sparse Graph-Structured Lasso Mixed Model for Genetic Association with Confounding Correction.
CoRR, 2017
Proceedings of the 2017 IEEE International Conference on Multimedia and Expo, 2017
Multiplex confounding factor correction for genomic association mapping with squared sparse linear mixed model.
Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017
Variable selection in heterogeneous datasets: A truncated-rank sparse linear mixed model with applications to genome-wide association studies.
Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017
2016
SeDMiD for Confusion Detection: Uncovering Mind State from Time Series Brain Wave Data.
CoRR, 2016
Select-Additive Learning: Improving Cross-individual Generalization in Multimodal Sentiment Analysis.
CoRR, 2016
Multiple confounders correction with regularized linear mixed effect models, with application in biological processes.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016
2015
A Survey: Time Travel in Deep Learning Space: An Introduction to Deep Learning Models and How Deep Learning Models Evolved from the Initial Ideas.
CoRR, 2015
CoRR, 2015
Evaluation of Protein-protein Interaction Predictors with Noisy Partially Labeled Data Sets.
CoRR, 2015
Learning structure in gene expression data using deep architectures, with an application to gene clustering.
Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine, 2015
2014
CoRR, 2014
2013
Proceedings of the Annual Symposium on Computing for Development, 2013
Proceedings of the Workshops at the 16th International Conference on Artificial Intelligence in Education AIED 2013, 2013