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Pietro Lió

67 papers · 2017–2026 · 9 conferences · across top CS/AI conferences

Achievements

🏃 Academic Marathon (8) 🗺️ Taxonomy Completionist (21) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (9) 🌉 Interdisciplinary Bridge 🐝 Cross-Pollinator (12) 👥 Mega-Team (22) 🏆 Grand Slam 🔬 Deep Specialist (25) 👑 Triple Crown 🧬 Topic Evolution 🏆 Keyword Champion (4) 💎 Century Club (65) ⚡ Prolific Year (6) 🚀 Conference Pioneer 🗃️ Keyword Collector (53) ❓ The Questioner 🔥 Unstoppable (9) 📈 Trend Setter

Conferences

NIPS (17) ICML (16) ICLR (13) AAAI (11) AISTATS (4) EMNLP (2) MIDL (2) CVPR (1) UAI (1)

Top co-authors

Pietro Barbiero (8) Ming Li (8) Cristian Bodnar (7) Mateja Jamnik (7) Petar Veličković (6) Yuguang Wang (5) Francesco Giannini (5) Nikola Simidjievski (4) Gabriele Corso (4) Alexander Norcliffe (4)

Keywords

graph neural network (18) hypergraph neural network (6) neural network (5) graph classification (4) representation learning (4) weisfeiler-lehman test (4) graph convolution (4) message passing (4) generative model (3) feature selection (3) gaussian process (3) framelet transform (3) spectral graph wavelet (2) protein structure (2) hyperbolic space (2) variational inference (2) simplicial complex (2) graph signal processing (2) graph embedding (2) geometric deep learning (2)

Papers

High-Pass Matters: Theoretical Insights and Sheaflet-Based Design for Hypergraph Neural Networks AAAI 2026
Permutation Equivariant Framelet-based Hypergraph Neural Networks AAAI 2026
Hierarchical Planning for Complex Tasks with Knowledge Graph-RAG and Symbolic Verification ICML 2025
Stochastic Encodings for Active Feature Acquisition ICML 2025
EduLLM: Leveraging Large Language Models and Framelet-Based Signed Hypergraph Neural Networks for Student Performance Prediction ICML 2025
NMA-tune: Generating Highly Designable and Dynamics Aware Protein Backbones ICML 2025
SPHINX: Structural Prediction using Hypergraph Inference Network ICML 2025
SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints ICLR 2025
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations ICLR 2025
gRNAde: Geometric Deep Learning for 3D RNA inverse design ICLR 2025
Deep Hypergraph Neural Networks with Tight Framelets AAAI 2025
Neural Reasoning for Sure Through Constructing Explainable Models AAAI 2025
When Hypergraph Meets Heterophily: New Benchmark Datasets and Baseline AAAI 2025
G-Adaptivity: optimised graph-based mesh relocation for finite element methods ICML 2025
Unsupervised Pretraining for Fact Verification by Language Model Distillation ICLR 2024
DEFT: Efficient Fine-tuning of Diffusion Models by Learning the Generalised $h$-transform NIPS 2024
Deep Equilibrium Algorithmic Reasoning NIPS 2024
HyperBERT: Mixing Hypergraph-Aware Layers with Language Models for Node Classification on Text-Attributed Hypergraphs EMNLP 2024
Dynamics-Informed Protein Design with Structure Conditioning ICLR 2024
Evaluating Representation Learning on the Protein Structure Universe ICLR 2024
How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing ICML 2024
Position: Topological Deep Learning is the New Frontier for Relational Learning ICML 2024
Weight Predictor Network with Feature Selection for Small Sample Tabular Biomedical Data AAAI 2023
Latent Graph Inference using Product Manifolds ICLR 2023
Global Explainability of GNNs via Logic Combination of Learned Concepts ICLR 2023
DBGDGM: Dynamic Brain Graph Deep Generative Model MIDL 2023
Graph classification Gaussian processes via spectral features UAI 2023
Interpretable Graph Networks Formulate Universal Algebra Conjectures NIPS 2023
Sheaf Hypergraph Networks NIPS 2023
SurvivalGAN: Generating Time-to-Event Data for Survival Analysis AISTATS 2023
SCOTCH and SODA: A Transformer Video Shadow Detection Framework CVPR 2023
Graph Denoising Diffusion for Inverse Protein Folding NIPS 2023
DBGSL: Dynamic Brain Graph Structure Learning MIDL 2023
Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis AAAI 2023
On the Expressive Power of Geometric Graph Neural Networks ICML 2023
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology ICML 2023
Interpretable Neural-Symbolic Concept Reasoning ICML 2023
Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off NIPS 2022
Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets AISTATS 2022
Bayesian Link Prediction with Deep Graph Convolutional Gaussian Processes AISTATS 2022
Extending Logic Explained Networks to Text Classification EMNLP 2022
Do We Need Anisotropic Graph Neural Networks? ICLR 2022
Composite Feature Selection Using Deep Ensembles NIPS 2022
SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks NIPS 2022
Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks NIPS 2022
Attentional Meta-learners for Few-shot Polythetic Classification ICML 2022
3D Infomax improves GNNs for Molecular Property Prediction ICML 2022
Graph Neural Networks with Adaptive Readouts NIPS 2022
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs NIPS 2022
Entropy-Based Logic Explanations of Neural Networks AAAI 2022
Algorithmic Concept-Based Explainable Reasoning AAAI 2022
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks ICML 2021
How Framelets Enhance Graph Neural Networks ICML 2021
Neural ODE Processes ICLR 2021
Neural Distance Embeddings for Biological Sequences NIPS 2021
Weisfeiler and Lehman Go Cellular: CW Networks NIPS 2021
Directional Graph Networks ICML 2021
Proximal Distilled Evolutionary Reinforcement Learning AAAI 2020
On Second Order Behaviour in Augmented Neural ODEs NIPS 2020
Abstract Diagrammatic Reasoning with Multiplex Graph Networks ICLR 2020
Principal Neighbourhood Aggregation for Graph Nets NIPS 2020
Constraining Variational Inference with Geometric Jensen-Shannon Divergence NIPS 2020
Path Integral Based Convolution and Pooling for Graph Neural Networks NIPS 2020
Unseen Word Representation by Aligning Heterogeneous Lexical Semantic Spaces AAAI 2019
Deep Graph Infomax ICLR 2019
Graph Attention Networks ICLR 2018
Bayesian Hybrid Matrix Factorisation for Data Integration AISTATS 2017