Computer-aided multi-objective optimization in small molecule discovery
Molecular discovery is a multi-objective optimization problem that requires identifying a
molecule or set of molecules that balance multiple, often competing, properties. Multi …
molecule or set of molecules that balance multiple, often competing, properties. Multi …
Reinforcement learning for generative ai: A survey
Deep Generative AI has been a long-standing essential topic in the machine learning
community, which can impact a number of application areas like text generation and …
community, which can impact a number of application areas like text generation and …
Coarsenconf: Equivariant coarsening with aggregated attention for molecular conformer generation
Molecular conformer generation (MCG) is an important task in cheminformatics and drug
discovery. The ability to efficiently generate low-energy 3D structures can avoid expensive …
discovery. The ability to efficiently generate low-energy 3D structures can avoid expensive …
Scalable fragment-based 3d molecular design with reinforcement learning
D Flam-Shepherd, A Zhigalin… - arxiv preprint arxiv …, 2022 - arxiv.org
Machine learning has the potential to automate molecular design and drastically accelerate
the discovery of new functional compounds. Towards this goal, generative models and …
the discovery of new functional compounds. Towards this goal, generative models and …
Improving small molecule generation using mutual information machine
We address the task of controlled generation of small molecules, which entails finding novel
molecules with desired properties under certain constraints (eg, similarity to a reference …
molecules with desired properties under certain constraints (eg, similarity to a reference …
Target-specific novel molecules with their recipe: Incorporating synthesizability in the design process
Application of Artificial intelligence (AI) in drug discovery has led to several success stories
in recent times. While traditional methods mostly relied upon screening large chemical …
in recent times. While traditional methods mostly relied upon screening large chemical …
Using Artificial Intelligence for de novo Drug Design and Retrosynthesis
R Arora, N Brosse, C Descamps… - Computational Drug …, 2024 - Wiley Online Library
Artificial intelligence (AI), driven by progress in deep learning, has emerged as a disruptive
technology across multiple industries. The development of AI approaches to de novo drug …
technology across multiple industries. The development of AI approaches to de novo drug …
Scalable Fragment-Based 3D Molecular Design with Reinforcement Learning
A Zhigalin - 2023 - dash.harvard.edu
Machine learning has the potential to automate molecular design and drastically accelerate
the discovery of new functional compounds. Towards this goal, generative models and …
the discovery of new functional compounds. Towards this goal, generative models and …
Similarity-Driven Regularization for Aligning Chemical and Latent Spaces in Molecular Design
J Yang, T Ma, Y **ao, Y Liu, Y Liu - openreview.net
Generative models play a pivotal role in molecular design by effectively generating target
molecules. Among these, generative models with latent space stand out due to their robust …
molecules. Among these, generative models with latent space stand out due to their robust …