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Jon Paul Janet
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2020 – today
- 2024
- [j9]Jiazhen He, Alessandro Tibo, Jon Paul Janet, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Ola Engkvist:
Evaluation of reinforcement learning in transformer-based molecular design. J. Cheminformatics 16(1): 95 (2024) - [j8]Hannes H. Loeffler, Jiazhen He, Alessandro Tibo, Jon Paul Janet, Alexey Voronov, Lewis H. Mervin, Ola Engkvist:
Reinvent 4: Modern AI-driven generative molecule design. J. Cheminformatics 16(1) (2024) - [j7]Yasmine Nahal, Janosch Menke, Julien Martinelli, Markus Heinonen, Mikhail Kabeshov, Jon Paul Janet, Eva Nittinger, Ola Engkvist, Samuel Kaski:
Human-in-the-loop active learning for goal-oriented molecule generation. J. Cheminformatics 16(1): 138 (2024) - [j6]Martin Priessner
, Richard J. Lewis
HSQC Spectra Simulation and Matching for Molecular Identification. J. Chem. Inf. Model. 64(8): 3180-3191 (2024) - [c2]Yasmine Nahal, Markus Heinonen, Mikhail Kabeshov, Jon Paul Janet, Eva Nittinger, Ola Engkvist, Samuel Kaski:
Towards Interpretable Models of Chemist Preferences for Human-in-the-Loop Assisted Drug Discovery. AIDD@ICANN 2024: 58-70 - [i6]Thomas Löhr, Michael Dodds, Lili Cao, Mikhail Kabeshov, Michele Assante, Jon Paul Janet, Marco Klähn, Ola Engkvist:
Navigating the Maize: Cyclic and conditional computational graphs for molecular simulation. CoRR abs/2402.10064 (2024) - [i5]David Buterez, Jon Paul Janet, Dino Oglic, Pietro Lio:
Masked Attention is All You Need for Graphs. CoRR abs/2402.10793 (2024) - [i4]Ross Irwin, Alessandro Tibo, Jon Paul Janet, Simon Olsson:
Efficient 3D Molecular Generation with Flow Matching and Scale Optimal Transport. CoRR abs/2406.07266 (2024) - [i3]Gökçe Geylan, Jon Paul Janet, Alessandro Tibo, Jiazhen He, Atanas Patronov, Mikhail Kabeshov, Florian David, Werngard Czechtizky, Ola Engkvist, Leonardo De Maria:
PepINVENT: Generative peptide design beyond the natural amino acids. CoRR abs/2409.14040 (2024) - 2023
- [j5]David Buterez
MF-PCBA: Multifidelity High-Throughput Screening Benchmarks for Drug Discovery and Machine Learning. J. Chem. Inf. Model. 63(9): 2667-2678 (2023) - 2022
- [j4]Jeff Guo
Improving de novo molecular design with curriculum learning. Nat. Mach. Intell. 4(6): 555-563 (2022) - [j3]Jeff Guo
Author Correction: Improving de novo molecular design with curriculum learning. Nat. Mach. Intell. 4(8): 731 (2022) - [c1]David Buterez, Jon Paul Janet, Steven J. Kiddle, Dino Oglic, Pietro Liò:
Graph Neural Networks with Adaptive Readouts. NeurIPS 2022 - [i2]David Buterez, Jon Paul Janet, Steven J. Kiddle, Dino Oglic, Pietro Liò:
Graph Neural Networks with Adaptive Readouts. CoRR abs/2211.04952 (2022) - 2021
- [j2]Jeff Guo, Jon Paul Janet, Matthias R. Bauer, Eva Nittinger
DockStream: a docking wrapper to enhance de novo molecular design. J. Cheminformatics 13(1): 89 (2021) - [j1]Jon Paul Janet
Reusability report: Learning the language of synthetic methods used in medicinal chemistry. Nat. Mach. Intell. 3(7): 572-575 (2021) - [i1]Daniel R. Harper, Aditya Nandy, Naveen Arunachalam, Chenru Duan, Jon Paul Janet, Heather J. Kulik:
Representations and Strategies for Transferable Machine Learning Models in Chemical Discovery. CoRR abs/2106.10768 (2021)
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