Showing 1–20 of 25 results
/ Date/ Name
Jul 28, 2021Attribute-based Explanations of Non-Linear Embeddings of High-Dimensional DataDec 17, 2024Modified UNIFAC 2.0 -- A Group-Contribution Method Completed with Machine LearningApr 10, 2026Automated Batch Distillation Process Simulation for a Large Hybrid Dataset for Deep Anomaly DetectionJul 25, 2024HANNA: Hard-constraint Neural Network for Consistent Activity Coefficient PredictionOct 20, 2025Formally Exploring Time-Series Anomaly Detection Evaluation MetricsDec 6, 2024Prediction of Activity Coefficients by Similarity-Based Imputation using Quantum-Chemical DescriptorsJan 27, 2025Using Large Language Models for Solving Thermodynamic ProblemsFeb 26, 2026Prediction of Diffusion Coefficients in Mixtures with Tensor CompletionJul 25, 2024Advancing Thermodynamic Group-Contribution Methods by Machine Learning: UNIFAC 2.0Apr 8, 2025MLPROP -- an open interactive web interface for thermophysical property prediction with machine learningJan 15, 2025GRAPPA -- A Hybrid Graph Neural Network for Predicting Pure Component Vapor PressuresSep 30, 2024SetPINNs: Set-based Physics-informed Neural NetworksJun 11, 2025Superstudent intelligence in thermodynamicsOct 20, 2025Batch Distillation Data for Developing Machine Learning Anomaly Detection MethodsFeb 17, 2022Hybridizing Physical and Data-driven Prediction Methods for Physicochemical PropertiesMar 10, 2023Deep Anomaly Detection on Tennessee Eastman Process DataJul 24, 2024KnowTD-An Actionable Knowledge Representation System for ThermodynamicsJun 12, 2024Balancing Molecular Information and Empirical Data in the Prediction of Physico-Chemical PropertiesOct 13, 2025DiffStyleTS: Diffusion Model for Style Transfer in Time SeriesNov 24, 2025CHAOS -- A Consistent Large-scale Database for Sigma-Profiles and Other Molecular Descriptors