Marwin Segler
Marwin Segler
Verified email at uni-muenster.de
Title
Cited by
Cited by
Year
Opportunities and obstacles for deep learning in biology and medicine
T Ching, DS Himmelstein, BK Beaulieu-Jones, AA Kalinin, BT Do, ...
Journal of The Royal Society Interface 15 (141), 20170387, 2018
4352018
Planning chemical syntheses with deep neural networks and symbolic AI
MHS Segler, M Preuss, MP Waller
Nature 555 (7698), 604-610, 2018
3672018
Generating focused molecule libraries for drug discovery with recurrent neural networks
MHS Segler, T Kogej, C Tyrchan, MP Waller
ACS central science 4 (1), 120-131, 2018
3032018
Neural‐symbolic machine learning for retrosynthesis and reaction prediction
MHS Segler, MP Waller
Chemistry–A European Journal 23 (25), 5966-5971, 2017
1472017
Modelling chemical reasoning to predict and invent reactions
MHS Segler, MP Waller
Chemistry–A European Journal 23 (25), 6118-6128, 2017
822017
GuacaMol: benchmarking models for de novo molecular design
N Brown, M Fiscato, MHS Segler, AC Vaucher
Journal of chemical information and modeling 59 (3), 1096-1108, 2019
482019
Exploring deep recurrent models with reinforcement learning for molecule design
D Neil, M Segler, L Guasch, M Ahmed, D Plumbley, M Sellwood, N Brown
222018
Towards" alphachem": Chemical synthesis planning with tree search and deep neural network policies
M Segler, M Preuß, MP Waller
arXiv preprint arXiv:1702.00020, 2017
172017
Silver-catalyzed 1, 3-dipolar cycloaddition of azomethine ylides with β-boryl acrylates
A López-Pérez, M Segler, J Adrio, JC Carretero
The Journal of organic chemistry 76 (6), 1945-1948, 2011
172011
A generative model for electron paths
J Bradshaw, MJ Kusner, B Paige, MHS Segler, JM Hernández-Lobato
arXiv preprint arXiv:1805.10970, 2018
16*2018
Dehydrogenative TEMPO‐Mediated Formation of Unstable Nitrones: Easy Access to N‐Carbamoyl Isoxazolines
A Gini, M Segler, D Kellner, OG Mancheno
Chemistry–A European Journal 21 (34), 12053-12060, 2015
162015
Artificial intelligence in drug discovery
MA Sellwood, M Ahmed, MHS Segler, N Brown
Future medicinal chemistry 10 (17), 2025-2028, 2018
132018
Defactor: Differentiable edge factorization-based probabilistic graph generation
R Assouel, M Ahmed, MH Segler, A Saffari, Y Bengio
arXiv preprint arXiv:1811.09766, 2018
82018
A model to search for synthesizable molecules
J Bradshaw, B Paige, MJ Kusner, M Segler, JM Hernández-Lobato
Advances in Neural Information Processing Systems, 7935-7947, 2019
62019
Opportunities And Obstacles For Deep Learning In Biology And Medicine. bioRxiv (2017)
T Ching, DS Himmelstein, BK Beaulieu-Jones, AA Kalinin, BT Do, ...
Retrieved from, 2017
42017
World Programs for Model-Based Learning and Planning in Compositional State and Action Spaces
MHS Segler
arXiv preprint arXiv:1912.13007, 2019
12019
Opportunities and obstacles for deep learning in biology and medicine: 2019 update
T Ching, DS Himmelstein, BK Beaulieu-Jones, AA Kalinin, BT Do, ...
Manubot, 2019
2019
Generating molecules via chemical reactions
J Bradshaw, MJ Kusner, B Paige, MHS Segler, JM Hernández-Lobato
Deep Generative Models for Highly Structured Data, DGS@ ICLR 2019 Workshop 7, 2019
2019
Robogenic chemistry
S Mcananama-Brereton, M Segler, M Waller
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 256, 2018
2018
Chemical Discovery as a Knowledge Graph Completion Problem
M Segler, MP Waller
AITP 2017, 2017
2017
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Articles 1–20