Meet ApplyKite Twin, the application assistant that learns with you

Meet your Twin, it learns with you

Your Twin learns with you

Launch week codes:30% off annual Pro20% off monthly Pro

Ends in00h00m00s

Haoyi Zhou

Beihang University

Research Interests

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Explore related searches

Articles (20)

Collaborators (2)

Denghui Zhang

Assistant Professor

Stevens Institute of Technology

UNITED STATES

Philip Yu

Distinguished Professor & Wexler Chair in Information Technology

University of Chicago

UNITED STATES

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Haoyi Zhou

Research Interests

Make your next move.

Explore related searches

Articles (20)

Collaborators (2)

Denghui Zhang

Philip Yu

Make your next move.

Haoyi Zhou

Research Interests

Make your next move.

Explore related searches

Articles (20)

A Survey on Foundation Models for Structured Data: Tabular, Time Series, and Graphs

Accelerating Influence Function Estimation for Large Language Models: A Practical Design

From Compression to Exploration: Active Querying Agent for 3D Physical Field Understanding

LatentFlow: Discovering Latent Continuous Dynamics across Channels for Multivariate Time Series Anomaly Detection

Leveraging LLMs for Semantic Correlation Enhancement in Spatial-temporal Imputation

Ionformer: A Data-Driven Deep Learning Baseline for Global Ionospheric TEC Forecasting

LEVER: Online Adaptive Sequence Learning Framework for High-Frequency Trading

ArcEDB: An Arbitrary-Precision Encrypted Database via (Amortized) Modular Homomorphic Encryption

A lightweight multi-layer perceptron for efficient multivariate time series forecasting

ColBetect: A Contrastive Learning Framework Featuring Dual Negative Samples for Anomaly Behavior Detection

Decoding Global Preferences: Temporal and Cooperative Dependency Modeling in Multi-Agent Preference-Based Reinforcement Learning

PE-Attack: On the Universal Positional Embedding Vulnerability in Transformer-based Models

PhoGAD: Graph-based Anomaly Behavior Detection with Persistent Homology Optimization

Screening and early warning system for chronic obstructive pulmonary disease with obstructive sleep apnoea based on the medical Internet of Things in three levels of healthcare: Protocol for a prospective, multicentre, observational cohort study

Self-Paced Unified Representation Learning for Hierarchical Multi-Label Classification

BadRes: Reveal the Backdoors Through Residual Connection

CLDG: Contrastive Learning on Dynamic Graphs

Colorectal cancer lymph node metastasis prediction with weakly supervised transformer-based multi-instance learning

Expanding the prediction capacity in long sequence time-series forecasting

Resonant Attack: Reveal Cross-Modal Vulnerability of CLIP,共振攻击：揭示跨模态模型 CLIP 的脆弱性

Collaborators (2)

Denghui Zhang

Philip Yu

Make your next move.