188 citations · 390 across the 13 of their papers we have counts for
14 papers
OpenWhistle: A Large-Scale Longitudinal Dataset and Benchmark of Bottlenose Dolphin Vocalizations
Faadil Mustun, Chiara Semenzin, Roberto Dessi +7
Recent advances in bioacoustics have been driven by large-scale corpora and standardized benchmarks, yet existing resources are overwhelmingly bird-centric and shallow per species,…
Model Merging Improves Zero-Shot Generalization in Bioacoustic Foundation Models
Davide Marincione, Donato Crisostomi, Roberto Dessi +2
Foundation models capable of generalizing across species and tasks represent a promising new frontier in bioacoustics, with NatureLM being one of the most prominent examples. While…
Deep Learning on Real-World Graphs
Emanuele Rossi
Graph Neural Networks (GNNs) have become a central tool for learning on graph-structured data, yet their applicability to real-world systems remains limited by key challenges such…
Temporal Graph Benchmark for Machine Learning on Temporal Graphs
Shenyang Huang, Farimah Poursafaei, Jacob Danovitch +7
We present the Temporal Graph Benchmark (TGB), a collection of challenging and diverse benchmark datasets for realistic, reproducible, and robust evaluation of machine learning mod…
Edge Directionality Improves Learning on Heterophilic Graphs
Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni +3
Graph Neural Networks (GNNs) have become the de-facto standard tool for modeling relational data. However, while many real-world graphs are directed, the majority of today's GNN mo…
Graph Neural Networks for Link Prediction with Subgraph Sketching
Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi +5
Many Graph Neural Networks (GNNs) perform poorly compared to simple heuristics on Link Prediction (LP) tasks. This is due to limitations in expressive power such as the inability t…
Learning to Infer Structures of Network Games
Emanuele Rossi, Federico Monti, Yan Leng +2
Strategic interactions between a group of individuals or organisations can be modelled as games played on networks, where a player's payoff depends not only on their actions but al…
Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization
Mirco Mutti, Riccardo De Santi, Emanuele Rossi +3
In the sequential decision making setting, an agent aims to achieve systematic generalization over a large, possibly infinite, set of environments. Such environments are modeled as…
On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features
Emanuele Rossi, Henry Kenlay, Maria I. Gorinova +3
While Graph Neural Networks (GNNs) have recently become the de facto standard for modeling relational data, they impose a strong assumption on the availability of the node or edge…
GRAND: Graph Neural Diffusion
Benjamin Paul Chamberlain, James Rowbottom, Maria Gorinova +3
We present Graph Neural Diffusion (GRAND) that approaches deep learning on graphs as a continuous diffusion process and treats Graph Neural Networks (GNNs) as discretisations of an…
Tuning Word2vec for Large Scale Recommendation Systems
Benjamin P. Chamberlain, Emanuele Rossi, Dan Shiebler +2
Word2vec is a powerful machine learning tool that emerged from Natural Lan-guage Processing (NLP) and is now applied in multiple domains, including recom-mender systems, forecastin…
Temporal Graph Networks for Deep Learning on Dynamic Graphs
Emanuele Rossi, Ben Chamberlain, Fabrizio Frasca +3
Graph Neural Networks (GNNs) have recently become increasingly popular due to their ability to learn complex systems of relations or interactions arising in a broad spectrum of pro…
SIGN: Scalable Inception Graph Neural Networks
Fabrizio Frasca, Emanuele Rossi, Davide Eynard +3
Graph representation learning has recently been applied to a broad spectrum of problems ranging from computer graphics and chemistry to high energy physics and social media. The po…
ncRNA Classification with Graph Convolutional Networks
Emanuele Rossi, Federico Monti, Michael Bronstein +1
Non-coding RNA (ncRNA) are RNA sequences which don't code for a gene but instead carry important biological functions. The task of ncRNA classification consists in classifying a gi…