Hao Wang

102

Papers

1,341

Total Citations

Papers (102)

Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model

NeurIPS 2017arXiv

Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks

NeurIPS 2016arXiv

Natural-Parameter Networks: A Class of Probabilistic Neural Networks

NeurIPS 2016arXiv

Beyond 3DMM Space: Towards Fine-grained 3D Face Reconstruction

Zero-1-to-3: Domain-Level Zero-Shot Cognitive Diagnosis via One Batch of Early-Bird Students towards Three Diagnostic Objectives

Agent4Edu: Generating Learner Response Data by Generative Agents for Intelligent Education Systems

Backdoor Federated Learning by Poisoning Backdoor-Critical Layers

Learning to Prompt Knowledge Transfer for Open-World Continual Learning

Revealing Key Details to See Differences: A Novel Prototypical Perspective for Skeleton-based Action Recognition

B-spine: Learning B-spline Curve Representation for Robust and Interpretable Spinal Curvature Estimation

OLinear: A Linear Model for Time Series Forecasting in Orthogonally Transformed Domain

MultiGO: Towards Multi-level Geometry Learning for Monocular 3D Textured Human Reconstruction

PhysSplat: Efficient Physics Simulation for 3D Scenes via MLLM-Guided Gaussian Splatting

Cautiously-Optimistic Knowledge Sharing for Cooperative Multi-Agent Reinforcement Learning

ADHMR: Aligning Diffusion-based Human Mesh Recovery via Direct Preference Optimization

LARGO: Latent Adversarial Reflection through Gradient Optimization for Jailbreaking LLMs

Enhancing Plausibility Evaluation for Generated Designs with Denoising Autoencoder

FIC-TSC: Learning Time Series Classification with Fisher Information Constraint

SSC-VAE: Structured Sparse Coding Based Variational Autoencoder for Detail Preserved Image Reconstruction

Sequence Complementor: Complementing Transformers for Time Series Forecasting with Learnable Sequences

CSPCL: Category Semantic Prior Contrastive Learning for Deformable DETR-Based Prohibited Item Detectors

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation

Design Graph Guided Element Importance-Aware Layout Generation with Multi-Modality Cascade Transformer

From Feature Interaction to Feature Generation: A Generative Paradigm of CTR Prediction Models

TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learning

Online Reconstruction of Indoor Scenes From RGB-D Streams

Real-Time Neural Style Transfer for Videos

Multi-Scale Location-Aware Kernel Representation for Object Detection

CosFace: Large Margin Cosine Loss for Deep Face Recognition

Decorrelated Adversarial Learning for Age-Invariant Face Recognition

Rethinking Knowledge Graph Propagation for Zero-Shot Learning

Learning Cross-Modal Embeddings With Adversarial Networks for Cooking Recipes and Food Images

SpSequenceNet: Semantic Segmentation Network on 4D Point Clouds

LAU-Net: Latitude Adaptive Upscaling Network for Omnidirectional Image Super-Resolution

Structured Multi-Level Interaction Network for Video Moment Localization via Language Query

Scene Text Retrieval via Joint Text Detection and Similarity Learning

Generative Interventions for Causal Learning

Face Forgery Detection by 3D Decomposition

OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks

Knowledge Mining With Scene Text for Fine-Grained Recognition

Bayesian Invariant Risk Minimization

DIP: Deep Inverse Patchmatch for High-Resolution Optical Flow

Semi-Supervised Wide-Angle Portraits Correction by Multi-Scale Transformer

StyleStudio: Text-Driven Style Transfer with Selective Control of Style Elements

TAPS3D: Text-Guided 3D Textured Shape Generation From Pseudo Supervision

Detecting Faces Using Inside Cascaded Contextual CNN

Adversarial Fine-Grained Composition Learning for Unseen Attribute-Object Recognition

Asymmetric Cross-Guided Attention Network for Actor and Action Video Segmentation From Natural Language Query

Paint Transformer: Feed Forward Neural Painting With Stroke Prediction

Adversarial Attacks Are Reversible With Natural Supervision

Self-Supervised Vessel Segmentation via Adversarial Learning

Context-Sensitive Temporal Feature Learning for Gait Recognition

GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning

A Good Student is Cooperative and Reliable: CNN-Transformer Collaborative Learning for Semantic Segmentation

Landscape Learning for Neural Network Inversion

Structure-Aware Generation Network for Recipe Generation from Images

"On Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization and Beyond"

Social ODE: Multi-agent Trajectory Forecasting with Neural Ordinary Differential Equations

Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting

NeurIPS 2015arXiv

Causal Transportability for Visual Recognition

RegGS: Unposed Sparse Views Gaussian Splatting with 3DGS Registration

Cracking Instance Jigsaw Puzzles: A Superior Alternative to Multiple Instance Learning for Whole Slide Image Analysis

Stealthy Backdoor Attack in Federated Learning via Adaptive Layer-wise Gradient Alignment

AirCache: Activating Inter-modal Relevancy KV Cache Compression for Efficient Large Vision-Language Model Inference

Knowledge-Guided Part Segmentation

Unified Open-World Segmentation with Multi-Modal Prompts

Outdoor Monocular SLAM with Global Scale-Consistent 3D Gaussian Pointmaps

Medical MLLM Is Vulnerable: Cross-Modality Jailbreak and Mismatched Attacks on Medical Multimodal Large Language Models

Manhattan Self-Attention Diffusion Residual Networks with Dynamic Bias Rectiﬁcation for BCI-based Few-Shot Learning

WHALE-FL: Wireless and Heterogeneity Aware Latency Efficient Federated Learning over Mobile Devices via Adaptive Subnetwork Scheduling

Knockoffs Inference for Partially Linear Models with Automatic Structure Discovery

Integrated Decision Gradients: Compute Your Attributions Where the Model Makes Its Decision

Fractional Deep Reinforcement Learning for Age-Minimal Mobile Edge Computing

Cheaper and Faster: Distributed Deep Reinforcement Learning with Serverless Computing

ViLT-CLIP: Video and Language Tuning CLIP with Multimodal Prompt Learning and Scenario-guided Optimization

DOCTR: Disentangled Object-Centric Transformer for Point Scene Understanding

Composite Active Learning: Towards Multi-Domain Active Learning with Theoretical Guarantees

FedST: Federated Style Transfer Learning for Non-IID Image Segmentation

CGI-DM: Digital Copyright Authentication for Diffusion Models via Contrasting Gradient Inversion

Near-Optimal Quantum Algorithm for Minimizing the Maximal Loss

Delving into Differentially Private Transformer

Probabilistic Conceptual Explainers: Trustworthy Conceptual Explanations for Vision Foundation Models

Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization

Motif-based Graph Self-Supervised Learning for Molecular Property Prediction

Analyzing the Generalization Capability of SGLD Using Properties of Gaussian Channels

Density-driven Regularization for Out-of-distribution Detection

Earthformer: Exploring Space-Time Transformers for Earth System Forecasting

Extrapolative Continuous-time Bayesian Neural Network for Fast Training-free Test-time Adaptation

Beyond Adult and COMPAS: Fair Multi-Class Prediction via Information Projection

Optimal Transport for Treatment Effect Estimation

Eliminating Domain Bias for Federated Learning in Representation Space

A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm

Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions

Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting

Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing

Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach

Adapting Fairness Interventions to Missing Values

UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction

Post-processing Private Synthetic Data for Improving Utility on Selected Measures

Analyzing Generalization of Neural Networks through Loss Path Kernels

PreDiff: Precipitation Nowcasting with Latent Diffusion Models

Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions