Pietro Lió

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