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Can Pre-trained Models Really Learn Better Molecular Representations for
  AI-aided Drug Discovery?

Can Pre-trained Models Really Learn Better Molecular Representations for AI-aided Drug Discovery?

21 August 2022
Ziqiao Zhang
Yatao Bian
Ailin Xie
Peng Han
Long-Kai Huang
Shuigeng Zhou
ArXivPDFHTML

Papers citing "Can Pre-trained Models Really Learn Better Molecular Representations for AI-aided Drug Discovery?"

15 / 15 papers shown
Title
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for
  AI-aided Drug Discovery -- A Focus on Affinity Prediction Problems with Noise
  Annotations
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery -- A Focus on Affinity Prediction Problems with Noise Annotations
Yuanfeng Ji
Lu Zhang
Jiaxiang Wu
Bing Wu
Long-Kai Huang
...
Ping Luo
Shuigeng Zhou
Junzhou Huang
Peilin Zhao
Yatao Bian
OOD
110
74
0
24 Jan 2022
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
SSL
AI4CE
74
256
0
03 Oct 2021
Frustratingly Easy Transferability Estimation
Frustratingly Easy Transferability Estimation
Long-Kai Huang
Ying Wei
Yu Rong
Qiang Yang
Junzhou Huang
76
58
0
17 Jun 2021
Do Transformers Really Perform Bad for Graph Representation?
Do Transformers Really Perform Bad for Graph Representation?
Chengxuan Ying
Tianle Cai
Shengjie Luo
Shuxin Zheng
Guolin Ke
Di He
Yanming Shen
Tie-Yan Liu
GNN
71
441
0
09 Jun 2021
Self-supervised Graph-level Representation Learning with Local and
  Global Structure
Self-supervised Graph-level Representation Learning with Local and Global Structure
Minghao Xu
Hang Wang
Bingbing Ni
Hongyu Guo
Jian Tang
SSL
32
209
0
08 Jun 2021
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs
Weihua Hu
Matthias Fey
Hongyu Ren
Maho Nakata
Yuxiao Dong
J. Leskovec
AI4CE
59
410
0
17 Mar 2021
LogME: Practical Assessment of Pre-trained Models for Transfer Learning
LogME: Practical Assessment of Pre-trained Models for Transfer Learning
Kaichao You
Yong Liu
Jianmin Wang
Mingsheng Long
72
180
0
22 Feb 2021
LEEP: A New Measure to Evaluate Transferability of Learned
  Representations
LEEP: A New Measure to Evaluate Transferability of Learned Representations
Cuong V Nguyen
Tal Hassner
Matthias Seeger
Cédric Archambeau
69
215
0
27 Feb 2020
Molecule Attention Transformer
Molecule Attention Transformer
Lukasz Maziarka
Tomasz Danel
Slawomir Mucha
Krzysztof Rataj
Jacek Tabor
Stanislaw Jastrzebski
58
169
0
19 Feb 2020
Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal
  Learning of Deep Spiking Neural Network
Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal Learning of Deep Spiking Neural Network
Haowen Fang
Amar Shrestha
Ziyi Zhao
Qinru Qiu
29
120
0
19 Feb 2020
SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug
  Discovery
SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery
Shion Honda
Shoi Shi
H. Ueda
MedIm
62
174
0
12 Nov 2019
Transferability and Hardness of Supervised Classification Tasks
Transferability and Hardness of Supervised Classification Tasks
Anh Tran
Cuong V Nguyen
Tal Hassner
164
165
0
21 Aug 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
SSL
AI4CE
96
1,396
0
29 May 2019
MoleculeNet: A Benchmark for Molecular Machine Learning
MoleculeNet: A Benchmark for Molecular Machine Learning
Zhenqin Wu
Bharath Ramsundar
Evan N. Feinberg
Joseph Gomes
C. Geniesse
Aneesh S. Pappu
K. Leswing
Vijay S. Pande
OOD
315
1,822
0
02 Mar 2017
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
Florian Schroff
Dmitry Kalenichenko
James Philbin
3DH
325
13,123
0
12 Mar 2015
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