| Img2Mol–accurate SMILES recognition from molecular graphical depictions DA Clevert, T Le, R Winter, F Montanari Chemical science 12 (42), 14174-14181, 2021 | 61 | 2021 |
| Parameterized hypercomplex graph neural networks for graph classification T Le, M Bertolini, F Noé, DA Clevert International Conference on Artificial Neural Networks, 204-216, 2021 | 44 | 2021 |
| Neuraldecipher–reverse-engineering extended-connectivity fingerprints (ECFPs) to their molecular structures T Le, R Winter, F Noé, DA Clevert Chemical science 11 (38), 10378-10389, 2020 | 41 | 2020 |
| Unsupervised learning of group invariant and equivariant representations R Winter, M Bertolini, T Le, F Noé, DA Clevert Advances in Neural Information Processing Systems 35, 31942-31956, 2022 | 34 | 2022 |
| Equivariant graph attention networks for molecular property prediction T Le, F Noé, DA Clevert arXiv preprint arXiv:2202.09891, 2022 | 18 | 2022 |
| Cell morphology-guided de novo hit design by conditioning GANs on phenotypic image features PAM Zapata, O Méndez-Lucio, T Le, CJ Beese, J Wichard, D Rouquié, ... Digital discovery 2 (1), 91-102, 2023 | 12 | 2023 |
| Representation learning on biomolecular structures using equivariant graph attention T Le, F Noe, DA Clevert Learning on Graphs Conference, 30: 1-30: 17, 2022 | 12 | 2022 |
| Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation T Le, J Cremer, F Noé, DA Clevert, K Schütt 12th International Conference on Learning Representations, 2023 | 8 | 2023 |
| A community effort in SARS‐CoV‐2 drug discovery J Schimunek, P Seidl, K Elez, T Hempel, T Le, F Noé, S Olsson, L Raich, ... Molecular Informatics 43 (1), e202300262, 2024 | 4 | 2024 |
| Multi-Objective Guidance via Importance Sampling for Target-Aware Diffusion-based De Novo Ligand Generation J Cremer, T Le, F Noe, DA Clevert, KT Schütt ICML'24 Workshop ML for Life and Material Science: From Theory to Industry …, 2024 | | 2024 |
| Latent-Guided Equivariant Diffusion for Controlled Structure-Based De Novo Ligand Generation T Le, J Cremer, DA Clevert, KT Schütt ICML'24 Workshop ML for Life and Material Science: From Theory to Industry …, 2024 | | 2024 |
| PILOT: Equivariant diffusion for pocket conditioned de novo ligand generation with multi-objective guidance via importance sampling J Cremer, T Le, F Noé, DA Clevert, KT Schütt arXiv preprint arXiv:2405.14925, 2024 | | 2024 |
| Going full hyper: hyperbolic and hypercomplex graph embeddings for ADMET modeling T Le, M Bertolini, MA Boef, F Montanari, DA Clevert Machine Learning for Molecules Workshop at NeurIPS 2020, 2020 | | 2020 |
| De novo drug design in continuous space T Le 10.5282/ubm/epub.70658, 2019 | | 2019 |
| Supplementary Information for Neuraldecipher-Reverse-engineering extended-connectivity fingerprints (ECFPs) to their molecular structures T Le, R Winter, F Noé, DA Clevert | | |
Djork-Arné ClevertPfizer, VP, Machine Learning Research在 pfizer.com 的电子邮件经过验证
