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Philippe Schwaller

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Related publications (32)

Molecular hypergraph neural networks

Graph neural networks (GNNs) have demonstrated promising performance across various chemistry-related tasks. However, conventional graphs only model the pairwise connectivity in molecules, failing to adequately represent higher order connections, such as m ...

Aip Publishing2024

Chemical education in digital chemistry

Philippe Schwaller

In this digital age where machine learning has won the Nobel Prizes in both Physics and Chemistry, it is ever more important to give chemistry students an educational advantage that will enable them to use the tools of artificial intelligence and machine l ...

CELL PRESS2024

Beam Enumeration: Probabilistic Explain-Ability for Sample Efficient Self-Conditioned Molecular Design

Philippe Schwaller, Jeff Guo

Generative molecular design has moved from proof-of-concept to real-world applicability, as marked by the surge in very recent papers reporting experimental validation. Key challenges in explainability and sample efficiency present opportunities to enhance ...

International Conference on Learning Representations, ICLR2024

Bayesian optimisation for additive screening and yield improvements - beyond one-hot encoding

Philippe Schwaller, Bojana Rankovic

Reaction additives are critical in dictating the outcomes of chemical processes making their effective screening vital for research. Conventional high-throughput experimentation tools can screen multiple reaction components rapidly. However, they are prohi ...

2024

14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon

Philippe Schwaller, Berend Smit, Kevin Maik Jablonka, Sauradeep Majumdar, Xiaoqi Zhang, Andres Camilo Marulanda Bran

Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronic ...

Royal Soc Chemistry2023

Accelerated chemical science with AI

Philippe Schwaller, Michele Ceriotti

In light of the pressing need for practical materials and molecular solutions to renewable energy and health problems, to name just two examples, one wonders how to accelerate research and development in the chemical sciences, so as to address the time it ...

Royal Soc Chemistry2023

Artificial intelligence for natural product drug discovery

Philippe Schwaller, Albert Hofstetter, Michael Alexander Skinnider, Florian Huber

Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to e ...

Nature Portfolio2023

Alchemical analysis of FDA approved drugs

Jean-Louis Reymond, Philippe Schwaller, Markus Orsi, Daniel Probst

Chemical space maps help visualize similarities within molecular sets. However, there are many different molecular similarity measures resulting in a confusing number of possible comparisons. To overcome this limitation, we exploit the fact that tools desi ...

2023

Bayesian Optimization for Chemical Reactions

Philippe Schwaller, Bojana Rankovic, Jeff Guo

Reaction optimization is challenging and traditionally delegated to domain experts who iteratively pro-pose increasingly optimal experiments. Problematically, the reaction landscape is complex and often requires hundreds of experiments to reach convergence ...

Swiss Chemical Soc2023

SELFIES and the future of molecular string representations

Philippe Schwaller, Berend Smit, Kevin Maik Jablonka

Artificial intelligence (AI) and machine learning (ML) are expanding in popularity for broad applications to challenging tasks in chemistry and materials science. Examples include the prediction of properties, the discovery of new reaction pathways, or the ...

ELSEVIER2022

FCC Physics Opportunities: Future Circular Collider Conceptual Design Report Volume 1

Manuel Bauer, Luca Rossi, Thomas Rizzo, François Robert, Jean-Michel Sallese, Pierluigi Bruzzone, Benedikt Moser, Mikhail Chapochnikov, Bernhard Auchmann, Jeffrey Alan Hubbell, Nicolas Andreini, Alban Sublet, Anatole von Lilienfeld, Mathias Oleg Knecht, Yu Bai, Jorg Wenninger, Michele Cascella, Marc-Olivier Sauvain, Tatiana Pieloni, Pablo Marcelo Perez Garcia, Rui Ning Wang, Leonid Rivkin, Hua Zhang, Xavier Buffat, Mingkui Wang, Andrea Wulzer, Martin Vogel, Nathalie Sophie Adeline Serra, Sandra Aumon, Alexandra Sarabando de Carvalho, Roberto Franceschini, Karin Irmgard Löw, Lucia Jimenez Rojo, Jie Gao, Giuseppe Montenero, Marco Drewes, Craig Nowell, Peter Michael Vogel, Shourya Dutta Gupta, Jairo Camilo Quijano Perez, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Insights into photovoltaic properties of ternary organic solar cells from phase diagrams

Philippe Schwaller, Roland Hany, Surendra Babu Anantharaman, Jakob Heier

The efficiency of ternary organic solar cells relies on the spontaneous establishment of a nanostructured network of donor and acceptor phases during film formation. A fundamental understanding of phase composition and arrangement and correlations to photo ...

2018

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Giovanni Migliorati

Andrea Thamm

Florian Patrick Marie Daniel De la Barre De Nanteuil

Andrey Denisov

Doohyun Kim

Frank Zimmermann

José Luis Abelleira Fernández

Alexej Grudiev

Philippe Schwaller

Fabio Avino

Darius Constantin Merk

Massimo Giovannozzi

Arturo Rivetti

Patrik Gonçalves Jorge

Francesco Cerutti

Ting-Yu Lee

Dragos-Adrian Seredinschi

Leonid Kahle

Juan Federico Esteban Müller

Javier Barranco Garcia

Roberto Contino

Eva Maria Rodriguez Franco

Beat Mueller

Rudiger Schmidt

Claudia Tambasco

Abdel Perez Hernandez

Shang-Jung Wu

José Luis Rivera Gutiérrez

Agnieszka Chmielinska

Lorena Gonçalves de Alcântara e Freitas Krikler

Candice Megan T Young

Rafael Amorim Leandro De Castro Amoedo

Xingyu Wu

Amirhossein Saba Shirvan

Wanderson Oliveira Da Silva

Mukesh Kumar Tripathi

Léon Van Riesen-Haupt

We review the physics opportunities of the Future Circular Collider, covering its e(+)e(-), pp, ep and heavy ion programmes. We describe the measurement capabilities of each FCC component, addressing the study of electroweak, Higgs and strong interactions, ...

2019