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Found 13 papers, 2 papers with code
Hybrid Polynomial Zonotopes: A Set Representation for Reachability Analysis in Hybrid Nonaffine Systems
Reachability analysis for hybrid nonaffine systems remains computationally challenging, as existing set representations--including constrained, polynomial, and hybrid zonotopes--either lose tightness under high-order nonaffine maps or suffer exponential blow-up after discrete jumps.
Data-Driven Reachability Analysis for Piecewise Affine Systems
Hybrid systems play a crucial role in modeling real-world applications where discrete and continuous dynamics interact, including autonomous vehicles, power systems, and traffic networks.
Chain of Attack: On the Robustness of Vision-Language Models Against Transfer-Based Adversarial Attacks
Pre-trained vision-language models (VLMs) have showcased remarkable performance in image and natural language understanding, such as image captioning and response generation.
The Mitochondrial Genome of Cathaya argyrophylla Reaches 18.99 Mb: Analysis of Super-Large Mitochondrial Genomes in Pinaceae
In this study, we sequenced and analyzed the mitochondrial genome of Cathaya argyrophylla, an endangered and endemic Pinaceae species, uncovering a genome size of 18. 99 Mb, meaning the largest mitochondrial genome reported to date.
UMOD: A Novel and Effective Urban Metro Origin-Destination Flow Prediction Method
Accurate prediction of metro Origin-Destination (OD) flow is essential for the development of intelligent transportation systems and effective urban traffic management.
AdaMR: Adaptable Molecular Representation for Unified Pre-training Strategy
We fine-tuned our proposed pre-trained model on six molecular property prediction tasks (MoleculeNet datasets) and two generative tasks (ZINC250K datasets), achieving state-of-the-art (SOTA) results on five out of eight tasks.
Developing a Multilingual Dataset and Evaluation Metrics for Code-Switching: A Focus on Hong Kong's Polylingual Dynamics
The traditional metrics overlook important factors such as latency in real-world applications and code-switching scenarios.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Key Gene Mining in Transcriptional Regulation for Specific Biological Processes with Small Sample Sizes Using Multi-network pipeline Transformer
Gene mining is an important topic in the field of life sciences, but traditional machine learning methods cannot consider the regulatory relationships between genes.
Spatio-Temporal Dynamic Graph Relation Learning for Urban Metro Flow Prediction
Second, we employ a dynamic graph relationship learning module to learn dynamic spatial relationships between metro stations without a predefined graph adjacency matrix.
HiSTGNN: Hierarchical Spatio-temporal Graph Neural Networks for Weather Forecasting
In this paper, we propose a novel Hierarchical Spatio-Temporal Graph Neural Network (HiSTGNN) to model cross-regional spatio-temporal correlations among meteorological variables in multiple stations.
Exploring Multi-dimensional Data via Subset Embedding
The core of the approach is a subset embedding network (SEN) that represents a group of subsets as uniformly-formatted embeddings.
Quality Control of Neuron Reconstruction Based on Deep Learning
To ensure the quality of reconstructed neurons and provide guidance for annotators to improve their efficiency, we propose a deep learning based quality control method for neuron reconstruction in this paper.
Urban flows prediction from spatial-temporal data using machine learning: A survey
Urban spatial-temporal flows prediction is of great importance to traffic management, land use, public safety, etc.
