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MaskMol: Knowledge-guided Molecular Image Pre-Training Framework for
  Activity Cliffs

MaskMol: Knowledge-guided Molecular Image Pre-Training Framework for Activity Cliffs

2 September 2024
Zhixiang Cheng
Hongxin Xiang
Pengsen Ma
Li Zeng
Xin Jin
Xixi Yang
Jianxin Lin
Yang Deng
Bosheng Song
Xinxin Feng
Changhui Deng
Xiangxiang Zeng
ArXiv (abs)PDFHTML

Papers citing "MaskMol: Knowledge-guided Molecular Image Pre-Training Framework for Activity Cliffs"

20 / 20 papers shown
Title
Why Deep Models Often cannot Beat Non-deep Counterparts on Molecular
  Property Prediction?
Why Deep Models Often cannot Beat Non-deep Counterparts on Molecular Property Prediction?
Jun Xia
Lecheng Zhang
Xiao Zhu
Stan Z. Li
103
3
0
30 Jun 2023
Keeping it Simple: Language Models can learn Complex Molecular
  Distributions
Keeping it Simple: Language Models can learn Complex Molecular Distributions
Daniel Flam-Shepherd
Kevin Zhu
A. Aspuru‐Guzik
215
148
0
06 Dec 2021
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViTTPM
477
7,819
0
11 Nov 2021
3D Infomax improves GNNs for Molecular Property Prediction
3D Infomax improves GNNs for Molecular Property Prediction
Hannes Stärk
Dominique Beaini
Gabriele Corso
Prudencio Tossou
Christian Dallago
Stephan Günnemann
Pietro Lio
AI4CE
92
208
0
08 Oct 2021
Pre-training Molecular Graph Representation with 3D Geometry
Pre-training Molecular Graph Representation with 3D Geometry
Shengchao Liu
Hanchen Wang
Weiyang Liu
Joan Lasenby
Hongyu Guo
Jian Tang
188
319
0
07 Oct 2021
Motif-based Graph Self-Supervised Learning for Molecular Property
  Prediction
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction
Zaixin Zhang
Qi Liu
Hao Wang
Chengqiang Lu
Chee-Kong Lee
SSLAI4CE
83
259
0
03 Oct 2021
ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for
  Property Prediction
ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for Property Prediction
Xiaomin Fang
Lihang Liu
Jieqiong Lei
Donglong He
Shanzhuo Zhang
Jingbo Zhou
Fan Wang
Hua Wu
Haifeng Wang
AI4CE
58
450
0
11 Jun 2021
ViLT: Vision-and-Language Transformer Without Convolution or Region
  Supervision
ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision
Wonjae Kim
Bokyung Son
Ildoo Kim
VLMCLIP
134
1,757
0
05 Feb 2021
An Image is Worth 16x16 Words: Transformers for Image Recognition at
  Scale
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy
Lucas Beyer
Alexander Kolesnikov
Dirk Weissenborn
Xiaohua Zhai
...
Matthias Minderer
G. Heigold
Sylvain Gelly
Jakob Uszkoreit
N. Houlsby
ViT
673
41,430
0
22 Oct 2020
ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular
  Property Prediction
ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction
Seyone Chithrananda
Gabriel Grand
Bharath Ramsundar
AI4CE
92
410
0
19 Oct 2020
Language Models are Few-Shot Learners
Language Models are Few-Shot Learners
Tom B. Brown
Benjamin Mann
Nick Ryder
Melanie Subbiah
Jared Kaplan
...
Christopher Berner
Sam McCandlish
Alec Radford
Ilya Sutskever
Dario Amodei
BDL
880
42,379
0
28 May 2020
RoBERTa: A Robustly Optimized BERT Pretraining Approach
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Yinhan Liu
Myle Ott
Naman Goyal
Jingfei Du
Mandar Joshi
Danqi Chen
Omer Levy
M. Lewis
Luke Zettlemoyer
Veselin Stoyanov
AIMat
677
24,541
0
26 Jul 2019
Strategies for Pre-training Graph Neural Networks
Strategies for Pre-training Graph Neural Networks
Weihua Hu
Bowen Liu
Joseph Gomes
Marinka Zitnik
Percy Liang
Vijay S. Pande
J. Leskovec
SSLAI4CE
118
1,415
0
29 May 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language
  Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin
Ming-Wei Chang
Kenton Lee
Kristina Toutanova
VLMSSLSSeg
1.8K
95,175
0
11 Oct 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
354
1,369
0
12 Feb 2018
Deeper Insights into Graph Convolutional Networks for Semi-Supervised
  Learning
Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning
Qimai Li
Zhichao Han
Xiao-Ming Wu
GNNSSL
194
2,830
0
22 Jan 2018
Graph Attention Networks
Graph Attention Networks
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
481
20,233
0
30 Oct 2017
Neural Message Passing for Quantum Chemistry
Neural Message Passing for Quantum Chemistry
Justin Gilmer
S. Schoenholz
Patrick F. Riley
Oriol Vinyals
George E. Dahl
598
7,488
0
04 Apr 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based
  Localization
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Ramprasaath R. Selvaraju
Michael Cogswell
Abhishek Das
Ramakrishna Vedantam
Devi Parikh
Dhruv Batra
FAtt
325
20,086
0
07 Oct 2016
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNNSSL
665
29,156
0
09 Sep 2016
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