November 15, 2018 editorial Open access Comment on “Predicting reaction performance in C–N cross-coupling using machine learning” Science DOI: 10.1126/science.aat8603 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 2 stored of 148 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Empowering Reactivity Predictions through Noise-Based Data Augmentation 2025 Journal of the American Chemical Society article Materials Science Machine Learning in Materials Science 15 citations AI is a viable alternative to high throughput screening: a 318-target study 2024 Scientific Reports article Computer Science Computational Drug Discovery Methods Open access 140 citations 2 results References 0