Analysis of Training and Seed Bias in Small Molecules Generated with a Conditional Graph-Based Variational Autoencoder─Insights for Practical AI-Driven Molecule Generation
- Seung-Gu Kang
- Joseph A. Morrone
- et al.
- 2022
- J. Chem. Inf. Model.
Paper
Publications
724 results for Generative AI
Pattern detection in the activation space for identifying synthesized content
- Celia Cintas
- Skyler Speakman
- et al.
- 2021
- Pattern Recognition Letters
PaperA Systematic Survey on Deep Generative Models for Graph Generation
- Xiaojie Guo
- Liang Zhao
- 2021
- IEEE TPAMI
PaperSeparation results between fixed-kernel and feature-learning probability metrics
- Carles Domingo-Enrich
- Youssef Mroueh
- 2021
- NeurIPS 2021
Conference paperA Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics
- Kai Xu
- Akash Srivastava
- et al.
- 2021
- NeurIPS 2021
Conference paperTargeted Neural Dynamical Modeling
- Cole Hurwitz
- Akash Srivastava
- et al.
- 2021
- NeurIPS 2021
Conference paperSample-efficient Generation of Novel Photo-acid Generator Molecules using a Deep Generative Model
- Samuel Hoffman
- Vijil Vijil
- et al.
- 2021
- NeurIPS 2021
Workshop paperBenchmarking deep generative models for diverse antibody sequence design
- Igor Melnyk
- Payel Das
- et al.
- 2021
- NeurIPS 2021
Workshop paperDynamics-Based Peptide-MHC Binding Optimization by a Convolutional Variational Autoencoder: A Use-Case Model for CASTELO
- David R. Bell
- Giacomo Domeniconi
- et al.
- 2021
- JCTC
PaperOpen Knowledge Graphs Canonicalization using Variational Autoencoders
- Sarthak Dash
- Gaetano Rossiello
- et al.
- 2021
- EMNLP 2021
Conference paper