Data engineering
All scientific publications in Area Science Park
A Comprehensive Analysis of Process Energy Consumption on Multi-Socket Systems with GPUs
Abstract: Robustly estimating energy consumption in High-Performance Computing (HPC) is essential for assessing the energy…
Molecular simulations to investigate the impact of N6-methylation in RNA recognition: Improving accuracy and precision…
Abstract N6-Methyladenosine (m6A) is a prevalent RNA post-transcriptional modification that plays crucial roles in RNA…
Detach-ROCKET: Sequential feature selection for time series classification with random convolutional kernels
Abstract: Time Series Classification (TSC) is essential in fields like medicine, environmental science, and finance,…
Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals
Abstract Interpretability research aims to bridge the gap between empirical success and our scientific understanding…
Emergent representations in networks trained with the Forward-Forward algorithm
Abstract The Backpropagation algorithm has often been criticised for its lack of biological realism. In…
Enhancing Multi-Tip Artifact Detection in STM Images Using Fourier Transform and Vision Transformers
Abstract We address the issue of multi-tip artifacts in Scanning Tunneling Microscopy (STM) images by…
Enhancing predictions of protein stability changes induced by single mutations using MSA-based language models
Abstract Protein language models offer a new perspective for addressing challenges in structural biology, while…
Protein family annotation for the Unified Human Gastrointestinal Proteome by DPCfam clustering
Abstract Technological advances in massively parallel sequencing have led to an exponential growth in the…
The geometry of hidden representations of large transformer models
Abstract Large transformers are powerful architectures used for self-supervised data analysis across various data types,…
Speeding‐up pruning for Artificial Neural Networks: Introducing Accelerated Iterative Magnitude Pruning
Abstract: In recent years, Artificial Neural Networks (ANNs) pruning has become the focal point of…
Investigating Similarity Metrics for Convolutional Neural Networks in the Case of Unstructured Pruning
Abstract: Deep Neural Networks (DNNs) are essential tools of modern science and technology. The current…
Hierarchical nucleation in deep neural networks
Abstract Deep convolutional networks (DCNs) learn meaningful representations where data that share the same abstract…