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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

24 January 2022
Yuanfeng Ji
Lu Zhang
Jiaxiang Wu
Bing Wu
Long-Kai Huang
Tingyang Xu
Yu Rong
Lanqing Li
Jie Ren
Ding Xue
Houtim Lai
Shaoyong Xu
Jing Feng
Wei Liu
Ping Luo
Shuigeng Zhou
Junzhou Huang
Peilin Zhao
Yatao Bian
    OOD
ArXivPDFHTML

Papers citing "DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery -- A Focus on Affinity Prediction Problems with Noise Annotations"

50 / 53 papers shown
Title
Soft causal learning for generalized molecule property prediction: An environment perspective
Soft causal learning for generalized molecule property prediction: An environment perspective
Limin Li
Kuo Yang
Wenjie Du
Pengkun Wang
Zhengyang Zhou
Yang Wang
OOD
AI4CE
56
0
0
07 May 2025
DivIL: Unveiling and Addressing Over-Invariance for Out-of- Distribution Generalization
DivIL: Unveiling and Addressing Over-Invariance for Out-of- Distribution Generalization
Jiaqi Wang
Yuhang Zhou
Zhixiong Zhang
Qiguang Chen
Yongqiang Chen
James Cheng
OODD
58
1
0
18 Feb 2025
Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy
Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy
Ruizhan Xue
Huimin Deng
Fang He
Maojun Wang
Zeyu Zhang
68
1
0
12 Feb 2025
GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation
GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation
Danny Wang
Ruihong Qiu
Guangdong Bai
Zi Huang
104
0
0
09 Feb 2025
Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
Song Wang
Xiaodong Yang
Rashidul Islam
Huiyuan Chen
Minghua Xu
Jundong Li
Yiwei Cai
OODD
52
2
0
07 Jan 2025
Causal-aware Graph Neural Architecture Search under Distribution Shifts
Causal-aware Graph Neural Architecture Search under Distribution Shifts
Peiwen Li
Xin Wang
Zeyang Zhang
Yi Qin
Ziwei Zhang
Jialong Wang
Yang Li
Wenwu Zhu
CML
OOD
62
4
0
31 Dec 2024
Subgraph Aggregation for Out-of-Distribution Generalization on Graphs
Subgraph Aggregation for Out-of-Distribution Generalization on Graphs
Bowen Liu
Haoyang Li
Shuning Wang
Shuo Nie
Shanghang Zhang
OODD
CML
69
0
0
29 Oct 2024
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation
Kexin Zhang
Shuhan Liu
Song Wang
Weili Shi
Chen Chen
Pan Li
Sheng R. Li
Jundong Li
Kaize Ding
OOD
47
2
0
25 Oct 2024
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning
Peter Eckmann
D. Wu
G. Heinzelmann
Michael K. Gilson
Rose Yu
AI4CE
40
0
0
15 Oct 2024
Teleporter Theory: A General and Simple Approach for Modeling
  Cross-World Counterfactual Causality
Teleporter Theory: A General and Simple Approach for Modeling Cross-World Counterfactual Causality
Jiangmeng Li
Bin Qin
Qirui Ji
Yi Li
Wenwen Qiang
Jianwen Cao
Fanjiang Xu
44
0
0
17 Jun 2024
How Interpretable Are Interpretable Graph Neural Networks?
How Interpretable Are Interpretable Graph Neural Networks?
Yongqiang Chen
Yatao Bian
Bo Han
James Cheng
46
4
0
12 Jun 2024
Adapting Large Multimodal Models to Distribution Shifts: The Role of
  In-Context Learning
Adapting Large Multimodal Models to Distribution Shifts: The Role of In-Context Learning
Guanglin Zhou
Zhongyi Han
Shiming Chen
Biwei Huang
Liming Zhu
Salman Khan
Xin Gao
Lina Yao
VLM
44
2
0
20 May 2024
Many-Shot In-Context Learning in Multimodal Foundation Models
Many-Shot In-Context Learning in Multimodal Foundation Models
Yixing Jiang
Jeremy Irvin
Ji Hun Wang
Muhammad Ahmed Chaudhry
Jonathan H. Chen
Andrew Y. Ng
VLM
43
28
0
16 May 2024
A Survey of Graph Neural Networks in Real world: Imbalance, Noise,
  Privacy and OOD Challenges
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges
Wei Ju
Siyu Yi
Yifan Wang
Zhiping Xiao
Zhengyan Mao
...
Senzhang Wang
Xinwang Liu
Xiao Luo
Philip S. Yu
Ming Zhang
AI4CE
36
35
0
07 Mar 2024
MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in
  Practical Generative Modeling
MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling
Peter Eckmann
D. Wu
G. Heinzelmann
Michael K. Gilson
Rose Yu
AI4CE
34
4
0
16 Feb 2024
GSINA: Improving Subgraph Extraction for Graph Invariant Learning via
  Graph Sinkhorn Attention
GSINA: Improving Subgraph Extraction for Graph Invariant Learning via Graph Sinkhorn Attention
Fangyu Ding
Haiyang Wang
Zhixuan Chu
Tianming Li
Zhaoping Hu
Junchi Yan
AI4CE
14
1
0
11 Feb 2024
Enhancing Neural Subset Selection: Integrating Background Information
  into Set Representations
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations
Binghui Xie
Yatao Bian
Kaiwen Zhou
Yongqiang Chen
Peilin Zhao
Bo Han
Wei Meng
James Cheng
16
1
0
05 Feb 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies
  and An Outlook
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook
Wenzhao Jiang
Hao Liu
Hui Xiong
CML
AI4CE
44
2
0
19 Dec 2023
Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution
  Generalization
Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution Generalization
Tianrui Jia
Haoyang Li
Cheng Yang
Tao Tao
Chuan Shi
OOD
33
17
0
18 Dec 2023
Environment-Aware Dynamic Graph Learning for Out-of-Distribution
  Generalization
Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization
Haonan Yuan
Qingyun Sun
Xingcheng Fu
Ziwei Zhang
Cheng Ji
Hao Peng
Jianxin Li
OOD
25
16
0
18 Nov 2023
RELand: Risk Estimation of Landmines via Interpretable Invariant Risk
  Minimization
RELand: Risk Estimation of Landmines via Interpretable Invariant Risk Minimization
Mateo Dulce Rubio
Siqi Zeng
Qi Wang
Didier Alvarado
Francisco Moreno
Hoda Heidari
Fei Fang
32
2
0
06 Nov 2023
Does Invariant Graph Learning via Environment Augmentation Learn
  Invariance?
Does Invariant Graph Learning via Environment Augmentation Learn Invariance?
Yongqiang Chen
Yatao Bian
Kaiwen Zhou
Binghui Xie
Bo Han
James Cheng
OOD
28
34
0
29 Oct 2023
Learning Invariant Molecular Representation in Latent Discrete Space
Learning Invariant Molecular Representation in Latent Discrete Space
Zhuang Xiang
Qiang Zhang
Keyan Ding
Yatao Bian
Xiao Wang
Jingsong Lv
Hongyang Chen
Huajun Chen
OOD
26
16
0
22 Oct 2023
Conformal Drug Property Prediction with Density Estimation under
  Covariate Shift
Conformal Drug Property Prediction with Density Estimation under Covariate Shift
Siddhartha Laghuvarapu
Zhen Lin
Jimeng Sun
20
4
0
18 Oct 2023
SGOOD: Substructure-enhanced Graph-Level Out-of-Distribution Detection
SGOOD: Substructure-enhanced Graph-Level Out-of-Distribution Detection
Zhihao Ding
Jieming Shi
Shiqi Shen
Xuequn Shang
Jiannong Cao
Zhipeng Wang
Zhi Gong
OODD
OOD
37
4
0
16 Oct 2023
Lo-Hi: Practical ML Drug Discovery Benchmark
Lo-Hi: Practical ML Drug Discovery Benchmark
Simon Steshin
VLM
15
7
0
10 Oct 2023
Towards out-of-distribution generalizable predictions of chemical
  kinetics properties
Towards out-of-distribution generalizable predictions of chemical kinetics properties
Zihao W. Wang
Yongqiang Chen
Yang Duan
Weijiang Li
Bo Han
James Cheng
Hanghang Tong
OOD
28
6
0
04 Oct 2023
MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph
  Contrastive Learning
MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph Contrastive Learning
Yun Zhu
Haizhou Shi
Zhenshuo Zhang
Siliang Tang
20
8
0
24 Jul 2023
OpenGDA: Graph Domain Adaptation Benchmark for Cross-network Learning
OpenGDA: Graph Domain Adaptation Benchmark for Cross-network Learning
Boshen Shi
Yongqing Wang
Fangda Guo
Jiangli Shao
Huawei Shen
Xueqi Cheng
OOD
AI4CE
25
4
0
21 Jul 2023
Drug Discovery under Covariate Shift with Domain-Informed Prior
  Distributions over Functions
Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions
Leo Klarner
Tim G. J. Rudner
M. Reutlinger
Torsten Schindler
Garrett M. Morris
Charlotte M. Deane
Yee Whye Teh
OOD
BDL
15
9
0
14 Jul 2023
Individual and Structural Graph Information Bottlenecks for
  Out-of-Distribution Generalization
Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalization
Ling Yang
Jiayi Zheng
Heyuan Wang
Zhongyi Liu
Zhilin Huang
Shenda Hong
Wentao Zhang
Bin Cui
22
13
0
28 Jun 2023
Symmetry-Informed Geometric Representation for Molecules, Proteins, and
  Crystalline Materials
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials
Shengchao Liu
Weitao Du
Yanjing Li
Zhuoxinran Li
Zhiling Zheng
...
Anima Anandkumar
C. Borgs
J. Chayes
Hongyu Guo
Jian Tang
AI4CE
33
19
0
15 Jun 2023
Joint Learning of Label and Environment Causal Independence for Graph
  Out-of-Distribution Generalization
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization
Shurui Gui
Meng Liu
Xiner Li
Youzhi Luo
Shuiwang Ji
CML
OOD
23
24
0
01 Jun 2023
Size Generalization of Graph Neural Networks on Biological Data:
  Insights and Practices from the Spectral Perspective
Size Generalization of Graph Neural Networks on Biological Data: Insights and Practices from the Spectral Perspective
Gao Li
Danai Koutra
Yujun Yan
21
1
0
24 May 2023
Learning Subpocket Prototypes for Generalizable Structure-based Drug
  Design
Learning Subpocket Prototypes for Generalizable Structure-based Drug Design
Zaixin Zhang
Qi Liu
27
34
0
22 May 2023
Large AI Models in Health Informatics: Applications, Challenges, and the
  Future
Large AI Models in Health Informatics: Applications, Challenges, and the Future
Jianing Qiu
Lin Li
Jiankai Sun
Jiachuan Peng
Peilun Shi
...
Bo Xiao
Wu Yuan
Ningli Wang
Dong Xu
Benny P. L. Lo
AI4MH
LM&MA
40
127
0
21 Mar 2023
Improving Domain Generalization with Domain Relations
Improving Domain Generalization with Domain Relations
Huaxiu Yao
Xinyu Yang
Xinyi Pan
Shengchao Liu
Pang Wei Koh
Chelsea Finn
OOD
AI4CE
50
8
0
06 Feb 2023
Multi-modal Molecule Structure-text Model for Text-based Retrieval and
  Editing
Multi-modal Molecule Structure-text Model for Text-based Retrieval and Editing
Shengchao Liu
Weili Nie
Chengpeng Wang
Jiarui Lu
Zhuoran Qiao
Ling Liu
Jian Tang
Chaowei Xiao
Anima Anandkumar
28
152
0
21 Dec 2022
ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug
  Discovery
ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery
Lanqing Li
Li Zeng
Zi-Chao Gao
Shen Yuan
Yatao Bian
...
Wei Liu
Hongteng Xu
Jia Li
P. Zhao
Pheng-Ann Heng
VLM
14
4
0
16 Sep 2022
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?
Ziqiao Zhang
Yatao Bian
Ailin Xie
Peng Han
Long-Kai Huang
Shuigeng Zhou
25
5
0
21 Aug 2022
Diversity Boosted Learning for Domain Generalization with Large Number
  of Domains
Diversity Boosted Learning for Domain Generalization with Large Number of Domains
Xinlin Leng
Xiaoying Tang
Yatao Bian
AI4CE
OOD
17
0
0
28 Jul 2022
GOOD: A Graph Out-of-Distribution Benchmark
GOOD: A Graph Out-of-Distribution Benchmark
Shurui Gui
Xiner Li
Limei Wang
Shuiwang Ji
OOD
22
115
0
16 Jun 2022
DRFLM: Distributionally Robust Federated Learning with Inter-client
  Noise via Local Mixup
DRFLM: Distributionally Robust Federated Learning with Inter-client Noise via Local Mixup
Bingzhe Wu
Zhipeng Liang
Yuxuan Han
Yatao Bian
P. Zhao
Junzhou Huang
OOD
FedML
11
3
0
16 Apr 2022
Learning Neural Set Functions Under the Optimal Subset Oracle
Learning Neural Set Functions Under the Optimal Subset Oracle
Zijing Ou
Tingyang Xu
Qinliang Su
Yingzhen Li
P. Zhao
Yatao Bian
BDL
16
9
0
03 Mar 2022
Out-Of-Distribution Generalization on Graphs: A Survey
Out-Of-Distribution Generalization on Graphs: A Survey
Haoyang Li
Xin Eric Wang
Ziwei Zhang
Wenwu Zhu
OOD
CML
21
96
0
16 Feb 2022
Recent Advances in Reliable Deep Graph Learning: Inherent Noise,
  Distribution Shift, and Adversarial Attack
Recent Advances in Reliable Deep Graph Learning: Inherent Noise, Distribution Shift, and Adversarial Attack
Jintang Li
Bingzhe Wu
Chengbin Hou
Guoji Fu
Yatao Bian
Liang Chen
Junzhou Huang
Zibin Zheng
OOD
AAML
24
6
0
15 Feb 2022
Chemical-Reaction-Aware Molecule Representation Learning
Chemical-Reaction-Aware Molecule Representation Learning
Hongwei Wang
Weijian Li
Xiaomeng Jin
Kyunghyun Cho
Heng Ji
Jiawei Han
Martin Burke
104
56
0
21 Sep 2021
DebiasedDTA: A Framework for Improving the Generalizability of
  Drug-Target Affinity Prediction Models
DebiasedDTA: A Framework for Improving the Generalizability of Drug-Target Affinity Prediction Models
Riza Ozccelik
Alperen Baug
Berk Atil
Melih Barsbey
Arzucan Özgür
Elif Özkirimli
AI4CE
6
0
0
04 Jul 2021
An Investigation of Why Overparameterization Exacerbates Spurious
  Correlations
An Investigation of Why Overparameterization Exacerbates Spurious Correlations
Shiori Sagawa
Aditi Raghunathan
Pang Wei Koh
Percy Liang
146
370
0
09 May 2020
Invariant Rationalization
Invariant Rationalization
Shiyu Chang
Yang Zhang
Mo Yu
Tommi Jaakkola
179
201
0
22 Mar 2020
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