94 citations · 266 across the 12 of their papers we have counts for
12 papers
CENTS: Generating synthetic electricity consumption time series for rare and unseen scenarios
Michael Fuest, Alfredo Cuesta, Kalyan Veeramachaneni
Recent breakthroughs in large-scale generative modeling have demonstrated the potential of foundation models in domains such as natural language, computer vision, and protein struc…
Real Time Evolvable Hardware for Optimal Reconfiguration of Cusp-Like Pulse Shapers
Juan Lanchares, Oscar Garnica, José L. Risco-Martín +3
The design of a cusp-like digital pulse shaper for particle energy measurements requires the definition of four parameters whose values are defined based on the nature of the shape…
Single Word Change is All You Need: Using LLMs to Create Synthetic Training Examples for Text Classifiers
Lei Xu, Sarah Alnegheimish, Laure Berti-Equille +2
In text classification, creating an adversarial example means subtly perturbing a few words in a sentence without changing its meaning, causing it to be misclassified by a classifi…
Modeling glycemia in humans by means of Grammatical Evolution
J. Ignacio Hidalgo, J. Manuel Colmenar, José L. Risco-Martín +4
Diabetes mellitus is a disease that affects to hundreds of millions of people worldwide. Maintaining a good control of the disease is critical to avoid severe long-term complicatio…
Boosting the 3D thermal-aware floorplanning problem through a master-worker parallel MOEA
Ignacio Arnaldo, Alfredo Cuesta-Infante, J. Manuel Colmenar +2
The increasing transistor scale integration poses, among others, the thermal-aware floorplanning problem; consisting of how to place the hardware components in order to reduce over…
R&R: Metric-guided Adversarial Sentence Generation
Lei Xu, Alfredo Cuesta-Infante, Laure Berti-Equille +1
Adversarial examples are helpful for analyzing and improving the robustness of text classifiers. Generating high-quality adversarial examples is a challenging task as it requires g…
TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks
Alexander Geiger, Dongyu Liu, Sarah Alnegheimish +2
Time series anomalies can offer information relevant to critical situations facing various fields, from finance and aerospace to the IT, security, and medical domains. However, det…
Robust Invisible Video Watermarking with Attention
Kevin Alex Zhang, Lei Xu, Alfredo Cuesta-Infante +1
The goal of video watermarking is to embed a message within a video file in a way such that it minimally impacts the viewing experience but can be recovered even if the video is re…
Towards Reducing Biases in Combining Multiple Experts Online
Yi Sun, Ivan Ramirez, Alfredo Cuesta-Infante +1
In many real life situations, including job and loan applications, gatekeepers must make justified and fair real-time decisions about a person's fitness for a particular opportunit…
Modeling Tabular data using Conditional GAN
Lei Xu, Maria Skoularidou, Alfredo Cuesta-Infante +1
Modeling the probability distribution of rows in tabular data and generating realistic synthetic data is a non-trivial task. Tabular data usually contains a mix of discrete and con…
SteganoGAN: High Capacity Image Steganography with GANs
Kevin Alex Zhang, Alfredo Cuesta-Infante, Lei Xu +1
Image steganography is a procedure for hiding messages inside pictures. While other techniques such as cryptography aim to prevent adversaries from reading the secret message, steg…
Learning Vine Copula Models For Synthetic Data Generation
Yi Sun, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
A vine copula model is a flexible high-dimensional dependence model which uses only bivariate building blocks. However, the number of possible configurations of a vine copula grows…