Representations and Strategies for Transferable Machine Learning Models in Chemical Discovery. - Daniel R. Harper; Aditya Nandy; Naveen Arunachalam; Chenru Duan; Jon Paul Janet; Heather J. Kulik (CoRR, 2021)

DockStream: a docking wrapper to enhance de novo molecular design. - Jeff Guo; Jon Paul Janet; Matthias R. Bauer; Eva Nittinger; Kathryn A. Giblin; Kostas Papadopoulos; Alexey Voronov; Atanas Patronov; Ola Engkvist; Christian Margreitter (J. Cheminformatics, 2021)

Reusability report: Learning the language of synthetic methods used in medicinal chemistry. - Jon Paul Janet; Anna Tomberg; Jonas Boström (Nat. Mach. Intell., 2021)

Graph Neural Networks with Adaptive Readouts. - David Buterez; Jon Paul Janet; Steven J. Kiddle; Dino Oglic; Pietro Liò (NeurIPS, 2022)

Improving de novo molecular design with curriculum learning. - Jeff Guo; Vendy Fialková; Juan Diego Arango; Christian Margreitter; Jon Paul Janet; Kostas Papadopoulos; Ola Engkvist; Atanas Patronov (Nat. Mach. Intell., 2022)

Author Correction: Improving de novo molecular design with curriculum learning. - Jeff Guo; Vendy Fialková; Juan Diego Arango; Christian Margreitter; Jon Paul Janet; Kostas Papadopoulos; Ola Engkvist; Atanas Patronov (Nat. Mach. Intell., 2022)

MF-PCBA: Multifidelity High-Throughput Screening Benchmarks for Drug Discovery and Machine Learning. - David Buterez; Jon Paul Janet; Steven J. Kiddle; Pietro Liò (J. Chem. Inf. Model., 2023)

Towards Interpretable Models of Chemist Preferences for Human-in-the-Loop Assisted Drug Discovery. - Yasmine Nahal; Markus Heinonen; Mikhail Kabeshov; Jon Paul Janet; Eva Nittinger; Ola Engkvist; Samuel Kaski (AIDD@ICANN, 2024)

Navigating the Maize: Cyclic and conditional computational graphs for molecular simulation. - Thomas Löhr; Michael Dodds; Lili Cao; Mikhail Kabeshov; Michele Assante; Jon Paul Janet; Marco Klähn; Ola Engkvist (CoRR, 2024)

Masked Attention is All You Need for Graphs. - David Buterez; Jon Paul Janet; Dino Oglic; Pietro Lio (CoRR, 2024)

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)

HSQC Spectra Simulation and Matching for Molecular Identification. - Martin Priessner; Richard J. Lewis; Magnus J. Johansson; Jonathan M. Goodman; Jon Paul Janet; Anna Tomberg (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)

Human-in-the-loop active learning for goal-oriented molecule generation. - Yasmine Nahal; Janosch Menke; Julien Martinelli; Markus Heinonen; Mikhail Kabeshov; Jon Paul Janet; Eva Nittinger; Ola Engkvist; Samuel Kaski (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)

Diverse Mini-Batch Selection in Reinforcement Learning for Efficient Chemical Exploration in de novo Drug Design. - Hampus Gummesson Svensson; Ola Engkvist; Jon Paul Janet; Christian Tyrchan; Morteza Haghir Chehreghani (CoRR, 2025)