Maintenance and emergency management with an integrated indoor/outdoor navigation support. - Pierfrancesco Bellini; Paolo Nesi; Matteo Simoncini; Alessandro Tibo (J. Vis. Lang. Comput., 2014)

A Network Architecture for Multi-Multi-Instance Learning. - Alessandro Tibo; Paolo Frasconi; Manfred Jaeger (ECML/PKDD (1), 2017)

Extended Pipeline for Content-Based Feature Engineering in Music Genre Recognition. - Tina Raissi; Alessandro Tibo; Paolo Bientinesi (ICASSP, 2018)

Off the Beaten Track: Using Deep Learning to Interpolate Between Music Genres. - Tijn Borghuis; Alessandro Tibo; Simone Conforti; Luca Canciello; Lorenzo Brusci; Paolo Frasconi (CoRR, 2018)

From Statistical Model Checking to Run-Time Monitoring Using a Bayesian Network Approach. - Manfred Jaeger; Kim G. Larsen; Alessandro Tibo (RV, 2020)

A general framework for defining and optimizing robustness. - Alessandro Tibo; Manfred Jaeger; Kim G. Larsen (CoRR, 2020)

Learning and Interpreting Multi-Multi-Instance Learning Networks. - Alessandro Tibo; Manfred Jaeger; Paolo Frasconi (J. Mach. Learn. Res., 2020)

Learning Aggregation Functions. - Giovanni Pellegrini; Alessandro Tibo; Paolo Frasconi; Andrea Passerini; Manfred Jaeger (IJCAI, 2021)

EXOGEM: Extending OpenAPI Generator for Monitoring of RESTful APIs. - Daniel Friis Holtebo; Jannik Lucas Sommer; Magnus Mølgaard Lund; Alessandro Tibo; Junior Dongo; Michele Albano (ICSOC Workshops, 2022)

Inducing Gaussian Process Networks. - Alessandro Tibo; Thomas Dyhre Nielsen (CoRR, 2022)

Graph Neural Networks for Microbial Genome Recovery. - Andre Lamurias; Alessandro Tibo; Katja Hose; Mads Albertsen; Thomas Dyhre Nielsen (CoRR, 2022)

Metagenomic Binning using Connectivity-constrained Variational Autoencoders. - Andre Lamurias; Alessandro Tibo; Katja Hose; Mads Albertsen; Thomas Dyhre Nielsen (ICML, 2023)

Efficient 3D Molecular Generation with Flow Matching and Scale Optimal Transport. - Ross Irwin; Alessandro Tibo; Jon Paul Janet; Simon Olsson (CoRR, 2024)

PepINVENT: Generative peptide design beyond the natural amino acids. - Gökçe Geylan; Jon Paul Janet; Alessandro Tibo; Jiazhen He; Atanas Patronov; Mikhail Kabeshov; Florian David; Werngard Czechtizky; Ola Engkvist; Leonardo De Maria (CoRR, 2024)

Challenge for Deep Learning: Protein Structure Prediction of Ligand-Induced Conformational Changes at Allosteric and Orthosteric Sites. - Gustav Olanders; Giulia Testa; Alessandro Tibo; Eva Nittinger; Christian Tyrchan (J. Chem. Inf. Model., 2024)

Do Chemformers Dream of Organic Matter? Evaluating a Transformer Model for Multistep Retrosynthesis. - Annie M. Westerlund; Siva Manohar Koki; Supriya Kancharla; Alessandro Tibo; Lakshidaa Saigiridharan; Mikhail Kabeshov; Rocío Mercado; Samuel Genheden (J. Chem. Inf. Model., 2024)

Evaluation of reinforcement learning in transformer-based molecular design. - Jiazhen He; Alessandro Tibo; Jon Paul Janet; Eva Nittinger; Christian Tyrchan; Werngard Czechtizky; Ola Engkvist (J. Cheminformatics, 2024)

Reinvent 4: Modern AI-driven generative molecule design. - Hannes H. Loeffler; Jiazhen He; Alessandro Tibo; Jon Paul Janet; Alexey Voronov; Lewis H. Mervin; Ola Engkvist (J. Cheminformatics, 2024)

SemlaFlow - Efficient 3D Molecular Generation with Latent Attention and Equivariant Flow Matching. - Ross Irwin; Alessandro Tibo; Jon Paul Janet; Simon Olsson (AISTATS, 2025)

FLOWR: Flow Matching for Structure-Aware De Novo, Interaction- and Fragment-Based Ligand Generation. - Julian Cremer; Ross Irwin; Alessandro Tibo; Jon Paul Janet; Simon Olsson; Djork-Arné Clevert (CoRR, 2025)