Investigating Explainability of Generative AI for Code through Scenario-based DesignJiao SunQ. Vera Liaoet al.2022IUI 2022
Learning exotic phases of matter via hidden Born MachinesKhadijeh NajafiAbigail McClain Gomezet al.2022APS March Meeting 2022
Understanding latent correlation-based multiview learning and self-supervision: An identifiability perspectiveQi LyuXiao Fuet al.2022ICLR 2022
Analysis of Training and Seed Bias in Small Molecules Generated with a Conditional Graph-Based Variational Autoencoder─Insights for Practical AI-Driven Molecule GenerationSeung-Gu KangJoseph A. Morroneet al.2022J. Chem. Inf. Model.
Pattern detection in the activation space for identifying synthesized contentCelia CintasSkyler Speakmanet al.2021Pattern Recognition Letters
A Systematic Survey on Deep Generative Models for Graph GenerationXiaojie GuoLiang Zhao2021IEEE TPAMI
Separation results between fixed-kernel and feature-learning probability metricsCarles Domingo-EnrichYoussef Mroueh2021NeurIPS 2021
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive PhysicsKai XuAkash Srivastavaet al.2021NeurIPS 2021
Benchmarking deep generative models for diverse antibody sequence designIgor MelnykPayel Daset al.2021NeurIPS 2021