7 papers
olBlend: Language-Guided Molecular Blend Retrieval with Mixture Odor Prediction
Dian Jin, Zhechang Chen, Qilin Liang +5
Converting open-ended natural-language odor descriptions into molecular mixtures that can be physically prepared from an available inventory remains an important challenge in compu…
A Novel Method with Encoder-Decoder for Cross-Sensor Adaptation in Surface Shape Sensing with Sparse Strain Sensors
Shuo Wang, Heng Luo, Dian Jin +1
Performance variations in sensor arrays, caused by intrinsic differences or installation conditions, can lead to inconsistent results during shape sensing. To obtain accurate resul…
Efficient Equivariant High-Order Crystal Tensor Prediction via Cartesian Local-Environment Many-Body Coupling
Dian Jin, Yancheng Yuan, Xiaoming Tao
End-to-end prediction of high-order crystal tensor properties from atomic structures remains challenging: while spherical-harmonic equivariant models are expressive, their Clebsch-…
Magnitude-Modulated Equivariant Adapter for Parameter-Efficient Fine-Tuning of Equivariant Graph Neural Networks
Dian Jin, Yancheng Yuan, Xiaoming Tao
Pretrained equivariant graph neural networks based on spherical harmonics offer efficient and accurate alternatives to computationally expensive ab-initio methods, yet adapting the…
Rotational Sampling: A Plug-and-Play Encoder for Rotation-Invariant 3D Molecular GNNs
Dian Jin
Graph neural networks (GNNs) have achieved remarkable success in molecular property prediction. However, traditional graph representations struggle to effectively encode the inhere…
Some Thoughts on Symbolic Transfer Entropy
Dian Jin
Transfer entropy is used to establish a measure of causal relationships between two variables. Symbolic transfer entropy, as an estimation method for transfer entropy, is widely ap…
Fitting an Elephant with Four non-Zero Parameters
Dian Jin, Junze Yuan
In 1953, Enrico Fermi criticized Dyson's model by quoting Johnny von Neumann: "With four parameters I can fit an elephant, and with five I can make him wiggle his trunk." So far, t…