13 citations · 15 across the 7 of their papers we have counts for
5 papers · 1 filter
GROOT: Effective Design of Biological Sequences with Limited Experimental Data
Thanh V. T. Tran, Nhat Khang Ngo, Viet Anh Nguyen +1
Latent space optimization (LSO) is a powerful method for designing discrete, high-dimensional biological sequences that maximize expensive black-box functions, such as wet lab expe…
Range-aware Positional Encoding via High-order Pretraining: Theory and Practice
Viet Anh Nguyen, Nhat Khang Ngo, Truong Son Hy
Unsupervised pre-training on vast amounts of graph data is critical in real-world applications wherein labeled data is limited, such as molecule properties prediction or materials…
E(3)-Equivariant Mesh Neural Networks
Thuan Trang, Nhat Khang Ngo, Daniel Levy +3
Triangular meshes are widely used to represent three-dimensional objects. As a result, many recent works have address the need for geometric deep learning on 3D mesh. However, we o…
Modeling Polypharmacy and Predicting Drug-Drug Interactions using Deep Generative Models on Multimodal Graphs
Nhat Khang Ngo, Truong Son Hy, Risi Kondor
Latent representations of drugs and their targets produced by contemporary graph autoencoder models have proved useful in predicting many types of node-pair interactions on large n…
Multiresolution Graph Transformers and Wavelet Positional Encoding for Learning Hierarchical Structures
Nhat Khang Ngo, Truong Son Hy, Risi Kondor
Contemporary graph learning algorithms are not well-defined for large molecules since they do not consider the hierarchical interactions among the atoms, which are essential to det…