Search Results for author:
Found 6 papers, 3 papers with code
Process Mining Embeddings: Learning Vector Representations for Petri Nets
The results demonstrate that PetriNet2Vec effectively captures the structural properties of process models, enabling accurate process classification and efficient process retrieval.
Tasks People Prompt: A Taxonomy of LLM Downstream Tasks in Software Verification and Falsification Approaches
Prompting has become one of the main approaches to leverage emergent capabilities of Large Language Models [Brown et al. NeurIPS 2020, Wei et al. TMLR 2022, Wei et al. NeurIPS 2022].
Catastrophic Forgetting in Deep Learning: A Comprehensive Taxonomy
Deep Learning models have achieved remarkable performance in tasks such as image classification or generation, often surpassing human accuracy.
Bag of Tricks for Long-Tail Visual Recognition of Animal Species in Camera-Trap Images
Although in most cases these rare species are the ones of interest to ecologists, they are often neglected when using deep-learning models because these models require a large number of images for the training.
Filtering Empty Camera Trap Images in Embedded Systems
Monitoring wildlife through camera traps produces a massive amount of images, whose a significant portion does not contain animals, being later discarded.
Discriminative Singular Spectrum Classifier with Applications on Bioacoustic Signal Recognition
Automatic analysis of bioacoustic signals is a fundamental tool to evaluate the vitality of our planet.
