80 citations · 228 across the 103 of their papers we have counts for
17 papers · 1 filter
SelfAI: A self-directed framework for long-horizon scientific discovery
Xiao Wu, Ting-Zhu Huang, Liang-Jian Deng +9
Scientific discovery increasingly entails long-horizon exploration of complex hypothesis spaces, yet most existing approaches emphasize final performance while offering limited ins…
QuAnTS: Question Answering on Time Series
Felix Divo, Maurice Kraus, Anh Q. Nguyen +5
Text offers intuitive access to information. This can, in particular, complement the density of numerical time series, thereby enabling improved interactions with time series model…
CHIPS: Efficient CLIP Adaptation via Curvature-aware Hybrid Influence-based Data Selection
Xinlin Zhuang, Yichen Li, Xiwei Liu +11
Adapting CLIP to vertical domains is typically approached by novel fine-tuning strategies or by continual pre-training (CPT) on large domain-specific datasets. Yet, data itself rem…
A Machine Learning Approach to Predict Biological Age and its Longitudinal Drivers
Nazira Dunbayeva, Yulong Li, Yutong Xie +1
Predicting an individual's aging trajectory is a central challenge in preventative medicine and bioinformatics. While machine learning models can predict chronological age from bio…
How Effectively Can Large Language Models Connect SNP Variants and ECG Phenotypes for Cardiovascular Risk Prediction?
Niranjana Arun Menon, Iqra Farooq, Yulong Li +4
Cardiovascular disease (CVD) prediction remains a tremendous challenge due to its multifactorial etiology and global burden of morbidity and mortality. Despite the growing availabi…
scAGC: Learning Adaptive Cell Graphs with Contrastive Guidance for Single-Cell Clustering
Huifa Li, Jie Fu, Xinlin Zhuang +6
Accurate cell type annotation is a crucial step in analyzing single-cell RNA sequencing (scRNA-seq) data, which provides valuable insights into cellular heterogeneity. However, due…
Rolling Ball Optimizer: Learning by ironing out loss landscape wrinkles
Mohammed Djameleddine Belgoumri, Mohamed Reda Bouadjenek, Hakim Hacid +2
Training large neural networks (NNs) requires optimizing high-dimensional data-dependent loss functions. The optimization landscape of these functions is often highly complex and t…
Enforcing Consistency and Fairness in Multi-level Hierarchical Classification with a Mask-based Output Layer
Shijing Chen, Shoaib Jameel, Mohamed Reda Bouadjenek +6
Traditional Multi-level Hierarchical Classification (MLHC) classifiers often rely on backbone models with independent output layers. This structure tends to overlook the hierar…
ScalingNoise: Scaling Inference-Time Search for Generating Infinite Videos
Haolin Yang, Feilong Tang, Ming Hu +8
Video diffusion models (VDMs) facilitate the generation of high-quality videos, with current research predominantly concentrated on scaling efforts during training through improvem…
GAMED: Knowledge Adaptive Multi-Experts Decoupling for Multimodal Fake News Detection
Lingzhi Shen, Yunfei Long, Xiaohao Cai +4
Multimodal fake news detection often involves modelling heterogeneous data sources, such as vision and language. Existing detection methods typically rely on fusion effectiveness a…
BTS: Building Timeseries Dataset: Empowering Large-Scale Building Analytics
Arian Prabowo, Xiachong Lin, Imran Razzak +4
Buildings play a crucial role in human well-being, influencing occupant comfort, health, and safety. Additionally, they contribute significantly to global energy consumption, accou…
A Gap in Time: The Challenge of Processing Heterogeneous IoT Data in Digitalized Buildings
Xiachong Lin, Arian Prabowo, Imran Razzak +4
The increasing demand for sustainable energy solutions has driven the integration of digitalized buildings into the power grid, leveraging Internet-of-Things (IoT) technologies to…
BayesJudge: Bayesian Kernel Language Modelling with Confidence Uncertainty in Legal Judgment Prediction
Ubaid Azam, Imran Razzak, Shelly Vishwakarma +3
Predicting legal judgments with reliable confidence is paramount for responsible legal AI applications. While transformer-based deep neural networks (DNNs) like BERT have demonstra…
From Uncertainty to Trust: Kernel Dropout for AI-Powered Medical Predictions
Ubaid Azam, Imran Razzak, Shelly Vishwakarma +3
AI-driven medical predictions with trustworthy confidence are essential for ensuring the responsible use of AI in healthcare applications. The growing capabilities of AI raise ques…
Progressive Class-Wise Attention (PCA) Approach for Diagnosing Skin Lesions
Asim Naveed, Syed S. Naqvi, Tariq M. Khan +1
Skin cancer holds the highest incidence rate among all cancers globally. The importance of early detection cannot be overstated, as late-stage cases can be lethal. Classifying skin…
Distributed Optimization of Graph Convolutional Network using Subgraph Variance
Taige Zhao, Xiangyu Song, Jianxin Li +2
In recent years, Graph Convolutional Networks (GCNs) have achieved great success in learning from graph-structured data. With the growing tendency of graph nodes and edges, GCN tra…
DepressionNet: A Novel Summarization Boosted Deep Framework for Depression Detection on Social Media
Hamad Zogan, Imran Razzak, Shoaib Jameel +1
Twitter is currently a popular online social media platform which allows users to share their user-generated content. This publicly-generated user data is also crucial to healthcar…