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1502.02072
Cited By
Massively Multitask Networks for Drug Discovery
6 February 2015
Bharath Ramsundar
S. Kearnes
Patrick F. Riley
D. Webster
D. Konerding
Vijay S. Pande
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Papers citing
"Massively Multitask Networks for Drug Discovery"
48 / 48 papers shown
Title
Limits of trust in medical AI
Joshua Hatherley
50
131
0
20 Mar 2025
Molecular Property Prediction Based on Graph Structure Learning
Bangyi Zhao
Weixia Xu
Jihong Guan
Shuigeng Zhou
19
7
0
28 Dec 2023
Beyond Mahalanobis-Based Scores for Textual OOD Detection
Pierre Colombo
Eduardo Dadalto Camara Gomes
Guillaume Staerman
Nathan Noiry
Pablo Piantanida
OODD
52
5
0
24 Nov 2022
Supervised Pretraining for Molecular Force Fields and Properties Prediction
Xiang Gao
Weihao Gao
Wen Xiao
Zhirui Wang
Chong Wang
Liang Xiang
AI4CE
25
8
0
23 Nov 2022
MULTIPAR: Supervised Irregular Tensor Factorization with Multi-task Learning
Yifei Ren
Jian Lou
Li Xiong
Joyce C. Ho
Xiaoqian Jiang
Sivasubramanium Bhavan
OOD
24
3
0
01 Aug 2022
ME-GAN: Learning Panoptic Electrocardio Representations for Multi-view ECG Synthesis Conditioned on Heart Diseases
Jintai Chen
Kuan-Yu Liao
Kun Wei
Haochao Ying
Danny Chen
Jian Wu
MedIm
21
18
0
21 Jul 2022
Nearly Minimax Algorithms for Linear Bandits with Shared Representation
Jiaqi Yang
Qi Lei
Jason D. Lee
S. Du
37
16
0
29 Mar 2022
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design
Yuanqi Du
Tianfan Fu
Jimeng Sun
Shengchao Liu
AI4CE
31
86
0
28 Mar 2022
Structured Multi-task Learning for Molecular Property Prediction
Shengchao Liu
Meng Qu
Zuobai Zhang
Huiyu Cai
Jian Tang
17
24
0
22 Feb 2022
Non-Stationary Representation Learning in Sequential Linear Bandits
Yuzhen Qin
Tommaso Menara
Samet Oymak
ShiNung Ching
Fabio Pasqualetti
OffRL
40
17
0
13 Jan 2022
Pre-training Molecular Graph Representation with 3D Geometry
Shengchao Liu
Hanchen Wang
Weiyang Liu
Joan Lasenby
Hongyu Guo
Jian Tang
126
302
0
07 Oct 2021
Molformer: Motif-based Transformer on 3D Heterogeneous Molecular Graphs
Fang Wu
Dragomir R. Radev
Huabin Xing
ViT
36
54
0
04 Oct 2021
SLAW: Scaled Loss Approximate Weighting for Efficient Multi-Task Learning
M. Crawshaw
Jana Kosecka
23
7
0
16 Sep 2021
Learning Attributed Graph Representations with Communicative Message Passing Transformer
Jianwen Chen
Shuangjia Zheng
Ying Song
Jiahua Rao
Yuedong Yang
30
46
0
19 Jul 2021
Artificial Intelligence in Drug Discovery: Applications and Techniques
Jianyuan Deng
Zhibo Yang
Iwao Ojima
Dimitris Samaras
Fusheng Wang
AI4TS
26
100
0
09 Jun 2021
Supervised Anomaly Detection via Conditional Generative Adversarial Network and Ensemble Active Learning
Zhi Chen
Jiang Duan
Li Kang
Guoping Qiu
AI4CE
47
31
0
24 Apr 2021
Artificial Intelligence Narratives: An Objective Perspective on Current Developments
Noah Klarmann
AI4TS
22
2
0
18 Mar 2021
Where is the Model Looking At?--Concentrate and Explain the Network Attention
Wenjia Xu
Jiuniu Wang
Yang Wang
Guangluan Xu
Wei Dai
Yirong Wu
XAI
24
17
0
29 Sep 2020
Probabilistic Active Meta-Learning
Jean Kaddour
Steindór Sæmundsson
M. Deisenroth
22
34
0
17 Jul 2020
Self-Supervised Graph Transformer on Large-Scale Molecular Data
Yu Rong
Yatao Bian
Tingyang Xu
Wei-yang Xie
Ying Wei
Wenbing Huang
Junzhou Huang
AI4CE
19
25
0
18 Jun 2020
Autonomous discovery in the chemical sciences part II: Outlook
Connor W. Coley
Natalie S. Eyke
K. Jensen
29
171
0
30 Mar 2020
A Survey of Deep Learning for Scientific Discovery
M. Raghu
Erica Schmidt
OOD
AI4CE
38
120
0
26 Mar 2020
SMILES-X: autonomous molecular compounds characterization for small datasets without descriptors
G. Lambard
Ekaterina Gracheva
27
20
0
20 Jun 2019
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules
Niklas W. A. Gebauer
M. Gastegger
Kristof T. Schütt
35
201
0
02 Jun 2019
Efficient Toxicity Prediction via Simple Features Using Shallow Neural Networks and Decision Trees
Abdul Karim
Avinash Mishra
M. A. Hakim Newton
A. Sattar
16
55
0
26 Jan 2019
Using Attribution to Decode Dataset Bias in Neural Network Models for Chemistry
Kevin McCloskey
Ankur Taly
Federico Monti
M. Brenner
Lucy J. Colwell
27
85
0
27 Nov 2018
KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images
I. Cortés-Ciriano
A. Bender
MedIm
30
51
0
22 Nov 2018
CheMixNet: Mixed DNN Architectures for Predicting Chemical Properties using Multiple Molecular Representations
Arindam Paul
Dipendra Jha
Reda Al-Bahrani
W. Liao
A. Choudhary
Ankit Agrawal
19
43
0
14 Nov 2018
MT-CGCNN: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Prediction
Soumya Sanyal
J. Balachandran
N. Yadati
Abhishek Kumar
Padmini Rajagopalan
Suchismita Sanyal
Partha P. Talukdar
24
48
0
14 Nov 2018
Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks
Clyde Fare
Lukas Turcani
Edward O. Pyzer-Knapp
26
13
0
17 Sep 2018
Multimodal Deep Neural Networks using Both Engineered and Learned Representations for Biodegradability Prediction
Garrett B. Goh
Khushmeen Sakloth
Charles Siegel
Abhinav Vishnu
J. Pfaendtner
HAI
28
11
0
13 Aug 2018
Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks
Yabo Ni
Dan Ou
Shichen Liu
Xiang Li
Wenwu Ou
Anxiang Zeng
Luo Si
30
139
0
28 May 2018
Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care
Patrick Schwab
E. Keller
C. Muroi
David J. Mack
C. Strässle
W. Karlen
21
23
0
14 Feb 2018
Metadynamics for Training Neural Network Model Chemistries: a Competitive Assessment
John E. Herr
Kun Yao
R. McIntyre
David W Toth
John A. Parkhill
20
63
0
19 Dec 2017
Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction
Garrett B. Goh
Charles Siegel
Abhinav Vishnu
Nathan Oken Hodas
21
90
0
07 Dec 2017
A trans-disciplinary review of deep learning research for water resources scientists
Chaopeng Shen
AI4CE
33
682
0
06 Dec 2017
Overcoming data scarcity with transfer learning
Maxwell Hutchinson
Erin Antono
Brenna M. Gibbons
S. Paradiso
Julia Ling
B. Meredig
18
81
0
02 Nov 2017
Ligand Pose Optimization with Atomic Grid-Based Convolutional Neural Networks
Matthew Ragoza
Lillian Turner
D. Koes
27
16
0
20 Oct 2017
Constrained Bayesian Optimization for Automatic Chemical Design
Ryan-Rhys Griffiths
José Miguel Hernández-Lobato
BDL
39
76
0
16 Sep 2017
Learning Graph-Level Representation for Drug Discovery
Junying Li
Deng Cai
Xiaofei He
GNN
AI4CE
23
115
0
12 Sep 2017
Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space
José Miguel Hernández-Lobato
James Requeima
Edward O. Pyzer-Knapp
Alán Aspuru-Guzik
33
177
0
06 Jun 2017
DeepCCI: End-to-end Deep Learning for Chemical-Chemical Interaction Prediction
Sunyoung Kwon
Sungroh Yoon
19
52
0
27 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
202
1,778
0
02 Mar 2017
Learning Deep Architectures for Interaction Prediction in Structure-based Virtual Screening
Adam Gonczarek
Jakub M. Tomczak
Szymon Zareba
J. Kaczmar
P. Dabrowski
Michał J. Walczak
19
68
0
23 Oct 2016
Modeling Industrial ADMET Data with Multitask Networks
S. Kearnes
Brian B. Goldman
Vijay S. Pande
9
55
0
28 Jun 2016
Deep Cross Residual Learning for Multitask Visual Recognition
Brendan Jou
Shih-Fu Chang
ObjD
29
91
0
05 Apr 2016
Molecular Graph Convolutions: Moving Beyond Fingerprints
S. Kearnes
Kevin McCloskey
Marc Berndl
Vijay S. Pande
Patrick F. Riley
GNN
52
1,435
0
02 Mar 2016
Toxicity Prediction using Deep Learning
Thomas Unterthiner
Andreas Mayr
G. Klambauer
Sepp Hochreiter
32
156
0
04 Mar 2015
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