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Drug Discovery under Covariate Shift with Domain-Informed Prior
  Distributions over Functions

Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions

14 July 2023
Leo Klarner
Tim G. J. Rudner
M. Reutlinger
Torsten Schindler
Garrett M. Morris
Charlotte M. Deane
Yee Whye Teh
    OODBDL
ArXiv (abs)PDFHTML

Papers citing "Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions"

23 / 23 papers shown
Title
Tractable Function-Space Variational Inference in Bayesian Neural
  Networks
Tractable Function-Space Variational Inference in Bayesian Neural Networks
Tim G. J. Rudner
Zonghao Chen
Yee Whye Teh
Y. Gal
122
44
0
28 Dec 2023
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
120
75
0
24 Jan 2022
E(n) Equivariant Graph Neural Networks
E(n) Equivariant Graph Neural Networks
Victor Garcia Satorras
Emiel Hoogeboom
Max Welling
113
1,033
0
19 Feb 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh
Shiori Sagawa
Henrik Marklund
Sang Michael Xie
Marvin Zhang
...
A. Kundaje
Emma Pierson
Sergey Levine
Chelsea Finn
Percy Liang
OOD
225
1,445
0
14 Dec 2020
Array Programming with NumPy
Array Programming with NumPy
Charles R. Harris
K. Millman
S. Walt
R. Gommers
Pauli Virtanen
...
Tyler Reddy
Warren Weckesser
Hameer Abbasi
C. Gohlke
T. Oliphant
156
14,995
0
18 Jun 2020
Distributionally Robust Neural Networks for Group Shifts: On the
  Importance of Regularization for Worst-Case Generalization
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization
Shiori Sagawa
Pang Wei Koh
Tatsunori B. Hashimoto
Percy Liang
OOD
108
1,248
0
20 Nov 2019
Invariant Risk Minimization
Invariant Risk Minimization
Martín Arjovsky
Léon Bottou
Ishaan Gulrajani
David Lopez-Paz
OOD
195
2,242
0
05 Jul 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive
  Uncertainty Under Dataset Shift
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
Yaniv Ovadia
Emily Fertig
Jie Jessie Ren
Zachary Nado
D. Sculley
Sebastian Nowozin
Joshua V. Dillon
Balaji Lakshminarayanan
Jasper Snoek
UQCV
175
1,702
0
06 Jun 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
116
1,415
0
29 May 2019
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
251
7,695
0
01 Oct 2018
A Survey on Deep Transfer Learning
A Survey on Deep Transfer Learning
Chuanqi Tan
F. Sun
Tao Kong
Wenchang Zhang
Chao Yang
Chunfang Liu
68
2,591
0
06 Aug 2018
UMAP: Uniform Manifold Approximation and Projection for Dimension
  Reduction
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
Leland McInnes
John Healy
James Melville
195
9,473
0
09 Feb 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
827
11,943
0
09 Mar 2017
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
337
1,837
0
02 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCVBDL
842
5,841
0
05 Dec 2016
Geometric deep learning: going beyond Euclidean data
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
813
3,293
0
24 Nov 2016
Automatic chemical design using a data-driven continuous representation
  of molecules
Automatic chemical design using a data-driven continuous representation of molecules
Rafael Gómez-Bombarelli
Jennifer N. Wei
David Duvenaud
José Miguel Hernández-Lobato
Benjamín Sánchez-Lengeling
Dennis Sheberla
J. Aguilera-Iparraguirre
Timothy D. Hirzel
Ryan P. Adams
Alán Aspuru-Guzik
3DV
174
2,939
0
07 Oct 2016
Deep CORAL: Correlation Alignment for Deep Domain Adaptation
Deep CORAL: Correlation Alignment for Deep Domain Adaptation
Baochen Sun
Kate Saenko
OOD
105
3,165
0
06 Jul 2016
Domain-Adversarial Training of Neural Networks
Domain-Adversarial Training of Neural Networks
Yaroslav Ganin
E. Ustinova
Hana Ajakan
Pascal Germain
Hugo Larochelle
François Laviolette
M. Marchand
Victor Lempitsky
GANOOD
390
9,515
0
28 May 2015
Weight Uncertainty in Neural Networks
Weight Uncertainty in Neural Networks
Charles Blundell
Julien Cornebise
Koray Kavukcuoglu
Daan Wierstra
UQCVBDL
192
1,892
0
20 May 2015
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
465
43,341
0
11 Feb 2015
Stochastic Variational Inference
Stochastic Variational Inference
Matt Hoffman
David M. Blei
Chong-Jun Wang
John Paisley
BDL
262
2,627
0
29 Jun 2012
A Tutorial on Spectral Clustering
A Tutorial on Spectral Clustering
U. V. Luxburg
290
10,543
0
01 Nov 2007
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