2 code implementations • 30 Mar 2024 • Zhishang Luo, Truong Son Hy, Puoya Tabaghi, Donghyeon Koh, Michael Defferrard, Elahe Rezaei, Ryan Carey, Rhett Davis, Rajeev Jain, Yusu Wang

Using the input and output data of the tools from past designs, one can attempt to build a machine learning model that predicts the outcome of a design in significantly shorter time than running the tool.

1 code implementation • 7 Feb 2024 • Thuan Trang, Nhat Khang Ngo, Daniel Levy, Thieu N. Vo, Siamak Ravanbakhsh, Truong Son Hy

Triangular meshes are widely used to represent three-dimensional objects.

1 code implementation • 24 Oct 2023 • Cong Dao Tran, Thong Bach, Truong Son Hy

Travelling Salesperson Problems (TSPs) and Vehicle Routing Problems (VRPs) have achieved reasonable improvement in accuracy and computation time with the adaptation of Machine Learning (ML) methods.

1 code implementation • 24 Oct 2023 • Truong Son Hy, Cong Dao Tran

We release our C++ implementations for metaheuristics such as EA, ILS and VNS along with the code for data generation and our generated data at https://github. com/HySonLab/Chinese_Postman_Problem

1 code implementation • 23 Oct 2023 • Khanh-Tung Tran, Truong Son Hy, Lili Jiang, Xuan-Son Vu

This integration provides rich indicators of pandemic dynamics through learning with temporal graph neural networks.

1 code implementation • 2 Aug 2023 • Nhat Khang Ngo, Truong Son Hy

To address this issue, we introduce TargetVAE, a target-aware variational auto-encoder that generates ligands with high binding affinities to arbitrary protein targets, guided by a novel multimodal deep neural network built based on graph Transformers as the prior for the generative model.

1 code implementation • 29 Jun 2023 • Ngoc-Dung Do, Truong Son Hy, Duy Khuong Nguyen

Second, we fit these graph structures and the input data into a Graph Convolutional Recurrent Network (GCRN) to train a forecasting model.

1 code implementation • 21 Jun 2023 • Duc Minh Nguyen, Minh Chau Vu, Tuan Anh Nguyen, Tri Huynh, Nguyen Tri Nguyen, Truong Son Hy

Turbulent flow simulation plays a crucial role in various applications, including aircraft and ship design, industrial process optimization, and weather prediction.

1 code implementation • 12 May 2023 • Viet Bach Nguyen, Truong Son Hy, Long Tran-Thanh, Nhung Nghiem

In this work, we propose a novel deep learning architecture named Attention-based Multiresolution Graph Neural Networks (ATMGNN) that learns to combine the spatial graph information, i. e. geographical data, with the temporal information, i. e. timeseries data of number of COVID-19 cases, to predict the future dynamics of the pandemic.

1 code implementation • 17 Feb 2023 • Duc Thien Nguyen, Manh Duc Tuan Nguyen, Truong Son Hy, Risi Kondor

To facilitate reliable and timely forecast for the human brain and traffic networks, we propose the Fast Temporal Wavelet Graph Neural Networks (FTWGNN) that is both time- and memory-efficient for learning tasks on timeseries data with the underlying graph structure, thanks to the theories of multiresolution analysis and wavelet theory on discrete spaces.

2 code implementations • 17 Feb 2023 • 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 determine the molecular properties of macromolecules.

Ranked #2 on Graph Regression on Peptides-struct

1 code implementation • 17 Feb 2023 • 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 networks, including drug-drug, drug-target, and target-target interactions.

1 code implementation • 27 Jan 2023 • Chen Cai, Truong Son Hy, Rose Yu, Yusu Wang

Graph Transformer (GT) recently has emerged as a new paradigm of graph learning algorithms, outperforming the previously popular Message Passing Neural Network (MPNN) on multiple benchmarks.

Ranked #8 on Node Classification on PascalVOC-SP

1 code implementation • 25 Jan 2023 • Cong Dao Tran, Nhut Huy Pham, Anh Nguyen, Truong Son Hy, Tu Vu

This paper presents ViDeBERTa, a new pre-trained monolingual language model for Vietnamese, with three versions - ViDeBERTa_xsmall, ViDeBERTa_base, and ViDeBERTa_large, which are pre-trained on a large-scale corpus of high-quality and diverse Vietnamese texts using DeBERTa architecture.

1 code implementation • 14 Sep 2022 • Nhat Khang Ngo, Truong Son Hy, Risi Kondor

However, most existing approaches model the node's latent spaces in which node distributions are rigid and disjoint; these limitations hinder the methods from generating new links among pairs of nodes.

no code implementations • 31 May 2022 • Minh Huynh Nguyen, Nghi D. Q. Bui, Truong Son Hy, Long Tran-Thanh, Tien N. Nguyen

We propose a novel method for code summarization utilizing Heterogeneous Code Representations (HCRs) and our specially designed HierarchyNet.

1 code implementation • 30 May 2022 • Truong Son Hy, Viet Bach Nguyen, Long Tran-Thanh, Risi Kondor

In this paper, we introduce Temporal Multiresolution Graph Neural Networks (TMGNN), the first architecture that both learns to construct the multiscale and multiresolution graph structures and incorporates the time-series signals to capture the temporal changes of the dynamic graphs.

1 code implementation • 2 Nov 2021 • Truong Son Hy, Risi Kondor

Multiresolution Matrix Factorization (MMF) is unusual amongst fast matrix factorization algorithms in that it does not make a low rank assumption.

2 code implementations • 2 Jun 2021 • Truong Son Hy, Risi Kondor

In this paper, we propose Multiresolution Equivariant Graph Variational Autoencoders (MGVAE), the first hierarchical generative model to learn and generate graphs in a multiresolution and equivariant manner.

1 code implementation • 8 Apr 2020 • Erik Henning Thiede, Truong Son Hy, Risi Kondor

Previous work on symmetric group equivariant neural networks generally only considered the case where the group acts by permuting the elements of a single vector.

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