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2212.01574
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Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS
3 December 2022
Gary Tom
Riley J. Hickman
Aniket N. Zinzuwadia
A. Mohajeri
Benjamín Sánchez-Lengeling
A. Aspuru‐Guzik
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Papers citing
"Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS"
21 / 21 papers shown
Title
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Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning
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Neil Band
Mark Collier
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Michael W. Dusenberry
...
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Jasper Snoek
Y. Gal
Dustin Tran
UQCV
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07 Jun 2021
Assigning Confidence to Molecular Property Prediction
AkshatKumar Nigam
R. Pollice
Matthew F. D. Hurley
Riley J. Hickman
Matteo Aldeghi
Naruki Yoshikawa
Seyone Chithrananda
Vincent A. Voelz
Alán Aspuru-Guzik
AI4CE
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23 Feb 2021
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness
Jeremiah Zhe Liu
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Shreyas Padhy
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Tania Bedrax-Weiss
Balaji Lakshminarayanan
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BDL
142
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17 Jun 2020
Uncertainty Quantification Using Neural Networks for Molecular Property Prediction
Lior Hirschfeld
Kyle Swanson
Kevin Kaichuang Yang
Regina Barzilay
Connor W. Coley
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20 May 2020
Gryffin: An algorithm for Bayesian optimization of categorical variables informed by expert knowledge
Florian Hase
Matteo Aldeghi
Riley J. Hickman
L. Roch
Alán Aspuru-Guzik
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108
0
26 Mar 2020
A Framework for Interdomain and Multioutput Gaussian Processes
Mark van der Wilk
Vincent Dutordoir
S. T. John
A. Artemev
Vincent Adam
J. Hensman
58
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02 Mar 2020
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
Tony Duan
Anand Avati
D. Ding
Khanh K. Thai
S. Basu
A. Ng
Alejandro Schuler
BDL
34
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08 Oct 2019
Deploying a Top-100 Supercomputer for Large Parallel Workloads: the Niagara Supercomputer
Marcelo Ponce
R. van Zon
Scott A. Northrup
D. Gruner
Joseph M. Chen
...
M. Saldarriaga
Vladimir Slavnic
Erik Spence
Ching-Hsing Yu
W. Peltier
49
166
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31 Jul 2019
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
153
1,688
0
06 Jun 2019
Evidential Deep Learning to Quantify Classification Uncertainty
Murat Sensoy
Lance M. Kaplan
M. Kandemir
OOD
UQCV
EDL
BDL
151
986
0
05 Jun 2018
Relational inductive biases, deep learning, and graph networks
Peter W. Battaglia
Jessica B. Hamrick
V. Bapst
Alvaro Sanchez-Gonzalez
V. Zambaldi
...
Pushmeet Kohli
M. Botvinick
Oriol Vinyals
Yujia Li
Razvan Pascanu
AI4CE
NAI
570
3,112
0
04 Jun 2018
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
Leland McInnes
John Healy
James Melville
152
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09 Feb 2018
A Network Perspective on Stratification of Multi-Label Data
Piotr Szymañski
Tomasz Kajdanowicz
38
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27 Apr 2017
Neural Message Passing for Quantum Chemistry
Justin Gilmer
S. Schoenholz
Patrick F. Riley
Oriol Vinyals
George E. Dahl
419
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0
04 Apr 2017
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
323
1,825
0
02 Mar 2017
GPflow: A Gaussian process library using TensorFlow
A. G. Matthews
Mark van der Wilk
T. Nickson
Keisuke Fujii
A. Boukouvalas
Pablo León-Villagrá
Zoubin Ghahramani
J. Hensman
GP
70
664
0
27 Oct 2016
Bayesian Optimization with Safety Constraints: Safe and Automatic Parameter Tuning in Robotics
Felix Berkenkamp
Andreas Krause
Angela P. Schoellig
126
283
0
14 Feb 2016
Deep Kernel Learning
A. Wilson
Zhiting Hu
Ruslan Salakhutdinov
Eric Xing
BDL
216
885
0
06 Nov 2015
Variational Dropout and the Local Reparameterization Trick
Diederik P. Kingma
Tim Salimans
Max Welling
BDL
196
1,510
0
08 Jun 2015
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