ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2201.09637
  4. Cited By
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"

15 / 15 papers shown
Title
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
46
0
0
09 Feb 2025
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
38
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
43
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
33
0
0
15 Oct 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
28
36
0
07 Mar 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
19
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
7
17
0
18 Dec 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
16
4
0
16 Oct 2023
GOOD: A Graph Out-of-Distribution Benchmark
GOOD: A Graph Out-of-Distribution Benchmark
Shurui Gui
Xiner Li
Limei Wang
Shuiwang Ji
OOD
6
115
0
16 Jun 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
92
46
0
21 Sep 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
128
368
0
09 May 2020
Invariant Rationalization
Invariant Rationalization
Shiyu Chang
Yang Zhang
Mo Yu
Tommi Jaakkola
179
197
0
22 Mar 2020
Deep Domain-Adversarial Image Generation for Domain Generalisation
Deep Domain-Adversarial Image Generation for Domain Generalisation
Kaiyang Zhou
Yongxin Yang
Timothy M. Hospedales
Tao Xiang
OOD
201
402
0
12 Mar 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx)
Out-of-Distribution Generalization via Risk Extrapolation (REx)
David M. Krueger
Ethan Caballero
J. Jacobsen
Amy Zhang
Jonathan Binas
Dinghuai Zhang
Rémi Le Priol
Aaron Courville
OOD
212
888
0
02 Mar 2020
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
152
1,748
0
02 Mar 2017
1