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Found 8 papers, 4 papers with code
Inverse Molecular Design with Multi-Conditional Diffusion Guidance
We extensively validate our model for multi-conditional polymer and small molecule generation.
DiffHybrid-UQ: Uncertainty Quantification for Differentiable Hybrid Neural Modeling
Addressing this gap, we introduce a novel method, DiffHybrid-UQ, for effective and efficient uncertainty propagation and estimation in hybrid neural differentiable models, leveraging the strengths of deep ensemble Bayesian learning and nonlinear transformations.
Probabilistic Physics-integrated Neural Differentiable Modeling for Isothermal Chemical Vapor Infiltration Process
Due to the complexities and limited experimental data of the isothermal CVI densification process, we have developed a data-driven predictive model using the physics-integrated neural differentiable (PiNDiff) modeling framework.
Semi-Supervised Graph Imbalanced Regression
The training data balance is achieved by (1) pseudo-labeling more graphs for under-represented labels with a novel regression confidence measurement and (2) augmenting graph examples in latent space for remaining rare labels after data balancing with pseudo-labels.
Data-Centric Learning from Unlabeled Graphs with Diffusion Model
A conventional approach is training a model with the unlabeled graphs on self-supervised tasks and then fine-tuning the model on the prediction tasks.
Graph Rationalization with Environment-based Augmentations
Rationale is defined as a subset of input features that best explains or supports the prediction by machine learning models.
Ranked #1 on
Graph Regression
on GlassTemp
Predicting Defects in Laser Powder Bed Fusion using in-situ Thermal Imaging Data and Machine Learning
In addition to using the thermal features of each voxel to predict its own state, the thermal features of neighboring voxels are also included as inputs.
Impact of Surface and Pore Characteristics on Fatigue Life of Laser Powder Bed Fusion Ti-6Al-4V Alloy Described by Neural Network Models
For the grit-blasted samples, the contour laser scan in the LPBF strategy led to a pore-depletion zone isolating surface and internal pores with different features.
