Ola Engkvist
Visar 42 publikationer
Temporal Evaluation of Uncertainty Quantification Under Distribution Shift
Registries in Machine Learning-Based Drug Discovery: A Shortcut to Code Reuse
Towards Interpretable Models of Chemist Preferences for Human-in-the-Loop Assisted Drug Discovery
Publishing neural networks in drug discovery might compromise training data privacy
Enhancing uncertainty quantification in drug discovery with censored regression labels
PepINVENT: generative peptide design beyond natural amino acids
Temporal Evaluation of Probability Calibration with Experimental Errors
Evaluation of reinforcement learning in transformer-based molecular design
Utilizing reinforcement learning for de novo drug design
QSARtuna: An Automated QSAR Modeling Platform for Molecular Property Prediction in Drug Design
Navigating the Maize: cyclic and conditional computational graphs for molecular simulation
Expanding the chemical space using a chemical reaction knowledge graph
Scoring the synthesizability of any novel non-natural amino acid
Exhaustive local chemical space exploration using a transformer model
Human-in-the-loop active learning for goal-oriented molecule generation
Metis: a python-based user interface to collect expert feedback for generative chemistry models
A data science roadmap for open science organizations engaged in early-stage drug discovery
Industry-Scale Orchestrated Federated Learning for Drug Discovery
Link-INVENT: generative linker design with reinforcement learning
De novo generated combinatorial library design
Prediction of the Chemical Context for Buchwald-Hartwig Coupling Reactions
Transformer-based molecular optimization beyond matched molecular pairs
Implications of topological imbalance for representation learning on biomedical knowledge graphs
LibINVENT: Reaction-based Generative Scaffold Decoration for in Silico Library Design
Using Active Learning to Develop Machine Learning Models for Reaction Yield Prediction
Improving de novo molecular design with curriculum learning
De Novo Drug Design Using Reinforcement Learning with Graph- Based Deep Generative Models
Evaluation guidelines for machine learning tools in the chemical sciences
A review of biomedical datasets relating to drug discovery: a knowledge graph perspective
Human-in-the-loop assisted de novo molecular design
Autonomous Drug Design with Multi-Armed Bandits
Exploring Graph Traversal Algorithms in Graph-Based Molecular Generation
Icolos: a workflow manager for structure-based post-processing of de novo generated small molecules
DockStream: a docking wrapper to enhance de novo molecular design
Parallel Capsule Networks for Classification of White Blood Cells
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