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06/08/2023
Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning
Advances in deep learning have greatly improved structure prediction of ...
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10/09/2022
Invertible Rescaling Network and Its Extensions
Image rescaling is a commonly used bidirectional operation, which first ...
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10/04/2022
One Transformer Can Understand Both 2D 3D Molecular Data
Unlike vision and language data which usually has a unique format, molec...
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08/19/2022
Predicting the protein-ligand affinity from molecular dynamics trajectories
The accurate protein-ligand binding affinity prediction is essential in ...
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07/20/2022
Quantized Training of Gradient Boosting Decision Trees
Recent years have witnessed significant success in Gradient Boosting Dec...
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05/26/2022
Your Transformer May Not be as Powerful as You Expect
Relative Positional Encoding (RPE), which encodes the relative distance ...
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03/09/2022
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets
This technical note describes the recent updates of Graphormer, includin...
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02/28/2022
An Empirical Study of Graphormer on Large-Scale Molecular Modeling Datasets
This technical note describes the recent updates of Graphormer, includin...
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06/23/2021
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding
The attention module, which is a crucial component in Transformer, canno...
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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...
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06/09/2021
Do Transformers Really Perform Bad for Graph Representation?
The Transformer architecture has become a dominant choice in many domain...
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05/10/2021
How could Neural Networks understand Programs?
Semantic understanding of programs is a fundamental problem for programm...
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02/16/2021
Revisiting Language Encoding in Learning Multilingual Representations
Transformer has demonstrated its great power to learn contextual word re...
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06/22/2020
Modeling Lost Information in Lossy Image Compression
Lossy image compression is one of the most commonly used operators for d...
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06/10/2020
MC-BERT: Efficient Language Pre-Training via a Meta Controller
Pre-trained contextual representations (e.g., BERT) have become the foun...
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05/12/2020
Invertible Image Rescaling
High-resolution digital images are usually downscaled to fit various dis...
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02/13/2020
Cross-Iteration Batch Normalization
A well-known issue of Batch Normalization is its significantly reduced e...
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02/12/2020
On Layer Normalization in the Transformer Architecture
The Transformer is widely used in natural language processing tasks. To ...
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09/19/2018
Capacity Control of ReLU Neural Networks by Basis-path Norm
Recently, path norm was proposed as a new capacity measure for neural ne...
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02/11/2018