Search Results for author:
Found 3 papers, 1 papers with code
Deep-learning Optical Flow Outperforms PIV in Obtaining Velocity Fields from Active Nematics
Deep learning-based optical flow (DLOF) extracts features in adjacent video frames with deep convolutional neural networks.
Solvent-Aware 2D NMR Prediction: Leveraging Multi-Tasking Training and Iterative Self-Training Strategies
Although significant progresses have been made in predicting one-dimensional (1D) NMR, two-dimensional (2D) NMR prediction via ML remains a challenge due to the lack of annotated NMR training datasets.
Asymmetric Contrastive Multimodal Learning for Advancing Chemical Understanding
Through practical tasks such as isomer discrimination and uncovering crucial chemical properties for drug discovery, ACML exhibits its capability to revolutionize chemical research and applications, providing a deeper understanding of chemical semantics of different modalities.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
