Guolin Ke | DeepAI

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∙ 04/24/2023

Uni-QSAR: an Auto-ML Tool for Molecular Property Prediction

Recently deep learning based quantitative structure-activity relationshi...

0 Zhifeng Gao, et al. ∙

∙ 02/14/2023

Do Deep Learning Models Really Outperform Traditional Approaches in Molecular Docking?

Molecular docking, given a ligand molecule and a ligand binding site (ca...

0 Yuejiang Yu, et al. ∙

∙ 02/14/2023

Do Deep Learning Methods Really Perform Better in Molecular Conformation Generation?

Molecular conformation generation (MCG) is a fundamental and important p...

0 Gengmo Zhou, et al. ∙

∙ 02/13/2023

Boosted ab initio Cryo-EM 3D Reconstruction with ACE-EM

The central problem in cryo-electron microscopy (cryo-EM) is to recover ...

0 Lin Yao, et al. ∙

∙ 02/12/2023

3D Molecular Generation via Virtual Dynamics

Structure-based drug design, i.e., finding molecules with high affinitie...

0 Shuqi Lu, et al. ∙

∙ 07/20/2022

Quantized Training of Gradient Boosting Decision Trees

Recent years have witnessed significant success in Gradient Boosting Dec...

5 Yu Shi, et al. ∙

∙ 04/13/2022

METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signals

We present an efficient method of pretraining large-scale autoencoding l...

0 Payal Bajaj, et al. ∙

∙ 03/09/2022

Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets

This technical note describes the recent updates of Graphormer, includin...

10 Yu Shi, et al. ∙

∙ 02/28/2022

An Empirical Study of Graphormer on Large-Scale Molecular Modeling Datasets

This technical note describes the recent updates of Graphormer, includin...

0 Yu Shi, et al. ∙

∙ 06/23/2021

Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding

The attention module, which is a crucial component in Transformer, canno...

9 Shengjie Luo, et al. ∙

∙ 06/15/2021

First Place Solution of KDD Cup 2021 OGB Large-Scale Challenge Graph-Level Track

In this technical report, we present our solution of KDD Cup 2021 OGB La...

7 Chengxuan Ying, et al. ∙

∙ 06/09/2021

Do Transformers Really Perform Bad for Graph Representation?

The Transformer architecture has become a dominant choice in many domain...

16 Chengxuan Ying, et al. ∙

∙ 05/10/2021

How could Neural Networks understand Programs?

Semantic understanding of programs is a fundamental problem for programm...

0 Dinglan Peng, et al. ∙

∙ 02/27/2021

Transformers with Competitive Ensembles of Independent Mechanisms

An important development in deep learning from the earliest MLPs has bee...

8 Alex Lamb, et al. ∙

∙ 02/25/2021

LazyFormer: Self Attention with Lazy Update

Improving the efficiency of Transformer-based language pre-training is a...

0 Chengxuan Ying, et al. ∙

∙ 02/18/2021

Less is More: Pre-training a Strong Siamese Encoder Using a Weak Decoder

Many real-world applications use Siamese networks to efficiently match t...

0 Shuqi Lu, et al. ∙

∙ 02/16/2021

Revisiting Language Encoding in Learning Multilingual Representations

Transformer has demonstrated its great power to learn contextual word re...

0 Shengjie Luo, et al. ∙

∙ 08/04/2020

Taking Notes on the Fly Helps BERT Pre-training

How to make unsupervised language pre-training more efficient and less r...

0 Qiyu Wu, et al. ∙

∙ 06/28/2020

Rethinking Positional Encoding in Language Pre-training

How to explicitly encode positional information into neural networks is ...

0 Guolin Ke, et al. ∙

∙ 06/28/2020

Rethinking the Positional Encoding in Language Pre-training

How to explicitly encode positional information into neural networks is ...

0 Guolin Ke, et al. ∙

∙ 06/10/2020

MC-BERT: Efficient Language Pre-Training via a Meta Controller

Pre-trained contextual representations (e.g., BERT) have become the foun...

0 Zhenhui Xu, et al. ∙

∙ 05/12/2020

Invertible Image Rescaling

High-resolution digital images are usually downscaled to fit various dis...

8 Mingqing Xiao, et al. ∙

∙ 08/25/2019

LightMC: A Dynamic and Efficient Multiclass Decomposition Algorithm

Multiclass decomposition splits a multiclass classification problem into...

0 Ziyu Liu, et al. ∙

∙ 07/16/2019

Light Multi-segment Activation for Model Compression

Model compression has become necessary when applying neural networks (NN...

0 Zhenhui Xu, et al. ∙

∙ 09/27/2018

Multi-task Learning for Financial Forecasting

Financial forecasting is challenging and attractive in machine learning....

0 Tao Ma, et al. ∙

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