13 citations · 28 across the 11 of their papers we have counts for
13 papers
Smart Timing for Mining: A Deep Learning Framework for Bitcoin Hardware ROI Prediction
Sithumi Wickramasinghe, Bikramjit Das, Dorien Herremans
Bitcoin mining hardware acquisition requires strategic timing due to volatile markets, rapid technological obsolescence, and protocol-driven revenue cycles. Despite mining's evolut…
HHNAS-AM: Hierarchical Hybrid Neural Architecture Search using Adaptive Mutation Policies
Anurag Tripathi, Ajeet Kumar Singh, Rajsabi Surya +4
Neural Architecture Search (NAS) has garnered significant research interest due to its capability to discover architectures superior to manually designed ones. Learning text repres…
End-to-End Text-to-SQL with Dataset Selection: Leveraging LLMs for Adaptive Query Generation
Anurag Tripathi, Vaibhav Patle, Abhinav Jain +4
Text-to-SQL bridges the gap between natural language and structured database language, thus allowing non-technical users to easily query databases. Traditional approaches model tex…
To Embody or Not: The Effect Of Embodiment On User Perception Of LLM-based Conversational Agents
Kyra Wang, Abhinaba Roy, Boon-Kiat Quek +2
Embodiment in conversational agents (CAs) refers to the physical or visual representation of these agents, which can significantly influence user perception and interaction. Limite…
Towards Unified Music Emotion Recognition across Dimensional and Categorical Models
Jaeyong Kang, Dorien Herremans
One of the most significant challenges in Music Emotion Recognition (MER) comes from the fact that emotion labels can be heterogeneous across datasets with regard to the emotion re…
Prevailing Research Areas for Music AI in the Era of Foundation Models
Megan Wei, Mateusz Modrzejewski, Aswin Sivaraman +1
Parallel to rapid advancements in foundation model research, the past few years have witnessed a surge in music AI applications. As AI-generated and AI-augmented music become incre…
DisfluencySpeech -- Single-Speaker Conversational Speech Dataset with Paralanguage
Kyra Wang, Dorien Herremans
Laughing, sighing, stuttering, and other forms of paralanguage do not contribute any direct lexical meaning to speech, but they provide crucial propositional context that aids sema…
DeepUnifiedMom: Unified Time-series Momentum Portfolio Construction via Multi-Task Learning with Multi-Gate Mixture of Experts
Joel Ong, Dorien Herremans
This paper introduces DeepUnifiedMom, a deep learning framework that enhances portfolio management through a multi-task learning approach and a multi-gate mixture of experts. The e…
Are We There Yet? A Brief Survey of Music Emotion Prediction Datasets, Models and Outstanding Challenges
Jaeyong Kang, Dorien Herremans
Deep learning models for music have advanced drastically in recent years, but how good are machine learning models at capturing emotion, and what challenges are researchers facing?…
Constructing Time-Series Momentum Portfolios with Deep Multi-Task Learning
Joel Ong, Dorien Herremans
A diversified risk-adjusted time-series momentum (TSMOM) portfolio can deliver substantial abnormal returns and offer some degree of tail risk protection during extreme market even…
Forecasting Bitcoin volatility spikes from whale transactions and CryptoQuant data using Synthesizer Transformer models
Dorien Herremans, Kah Wee Low
The cryptocurrency market is highly volatile compared to traditional financial markets. Hence, forecasting its volatility is crucial for risk management. In this paper, we investig…
Deep Neural Network Based Respiratory Pathology Classification Using Cough Sounds
Balamurali B T, Hwan Ing Hee, Saumitra Kapoor +5
Intelligent systems are transforming the world, as well as our healthcare system. We propose a deep learning-based cough sound classification model that can distinguish between chi…
Hit Song Prediction Based on Early Adopter Data and Audio Features
Dorien Herremans, Tom Bergmans
Billions of USD are invested in new artists and songs by the music industry every year. This research provides a new strategy for assessing the hit potential of songs, which can he…