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HOList: An Environment for Machine Learning of Higher-Order Theorem
  Proving

HOList: An Environment for Machine Learning of Higher-Order Theorem Proving

5 April 2019
Kshitij Bansal
Sarah M. Loos
M. Rabe
Christian Szegedy
S. Wilcox
    AIMat
ArXivPDFHTML

Papers citing "HOList: An Environment for Machine Learning of Higher-Order Theorem Proving"

19 / 19 papers shown
Title
GamePad: A Learning Environment for Theorem Proving
GamePad: A Learning Environment for Theorem Proving
Daniel Huang
Prafulla Dhariwal
D. Song
Ilya Sutskever
76
110
0
02 Jun 2018
Reinforcement Learning of Theorem Proving
Reinforcement Learning of Theorem Proving
C. Kaliszyk
Josef Urban
Henryk Michalewski
Miroslav Olsák
34
148
0
19 May 2018
Learning to Reason with HOL4 tactics
Learning to Reason with HOL4 tactics
Thibault Gauthier
C. Kaliszyk
Josef Urban
57
77
0
02 Apr 2018
Premise Selection for Theorem Proving by Deep Graph Embedding
Premise Selection for Theorem Proving by Deep Graph Embedding
Mingzhe Wang
Yihe Tang
Jian Wang
Jia Deng
58
133
0
28 Sep 2017
HolStep: A Machine Learning Dataset for Higher-order Logic Theorem
  Proving
HolStep: A Machine Learning Dataset for Higher-order Logic Theorem Proving
C. Kaliszyk
François Chollet
Christian Szegedy
52
82
0
01 Mar 2017
Deep Network Guided Proof Search
Deep Network Guided Proof Search
Sarah M. Loos
G. Irving
Christian Szegedy
C. Kaliszyk
AIMat
68
159
0
24 Jan 2017
WaveNet: A Generative Model for Raw Audio
WaveNet: A Generative Model for Raw Audio
Aaron van den Oord
Sander Dieleman
Heiga Zen
Karen Simonyan
Oriol Vinyals
Alex Graves
Nal Kalchbrenner
A. Senior
Koray Kavukcuoglu
DiffM
379
7,389
0
12 Sep 2016
Holophrasm: a neural Automated Theorem Prover for higher-order logic
Holophrasm: a neural Automated Theorem Prover for higher-order logic
Daniel Whalen
AIMat
61
50
0
08 Aug 2016
SQuAD: 100,000+ Questions for Machine Comprehension of Text
SQuAD: 100,000+ Questions for Machine Comprehension of Text
Pranav Rajpurkar
Jian Zhang
Konstantin Lopyrev
Percy Liang
RALM
256
8,124
0
16 Jun 2016
DeepMath - Deep Sequence Models for Premise Selection
DeepMath - Deep Sequence Models for Premise Selection
Alexander A. Alemi
François Chollet
N. Eén
G. Irving
Christian Szegedy
Josef Urban
LRM
AIMat
52
229
0
14 Jun 2016
Premise Selection and External Provers for HOL4
Premise Selection and External Provers for HOL4
Thibault Gauthier
C. Kaliszyk
25
47
0
11 Sep 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.7K
150,006
0
22 Dec 2014
Machine Learning of Coq Proof Guidance: First Experiments
Machine Learning of Coq Proof Guidance: First Experiments
C. Kaliszyk
L. Mamane
Josef Urban
LRM
25
17
0
20 Oct 2014
Microsoft COCO: Common Objects in Context
Microsoft COCO: Common Objects in Context
Nayeon Lee
Michael Maire
Serge J. Belongie
Lubomir Bourdev
Ross B. Girshick
James Hays
Pietro Perona
Deva Ramanan
C. L. Zitnick
Piotr Dollár
ObjD
391
43,619
0
01 May 2014
Machine Learner for Automated Reasoning 0.4 and 0.5
Machine Learner for Automated Reasoning 0.4 and 0.5
C. Kaliszyk
Josef Urban
J. Vyskočil
LRM
59
23
0
11 Feb 2014
Learning-assisted Theorem Proving with Millions of Lemmas
Learning-assisted Theorem Proving with Millions of Lemmas
C. Kaliszyk
Josef Urban
73
47
0
11 Feb 2014
MizAR 40 for Mizar 40
MizAR 40 for Mizar 40
C. Kaliszyk
Josef Urban
VLM
AI4CE
LRM
AIMat
101
135
0
10 Oct 2013
Learning-Assisted Automated Reasoning with Flyspeck
Learning-Assisted Automated Reasoning with Flyspeck
C. Kaliszyk
Josef Urban
LRM
78
162
0
29 Nov 2012
Premise Selection for Mathematics by Corpus Analysis and Kernel Methods
Premise Selection for Mathematics by Corpus Analysis and Kernel Methods
Jesse Alama
Tom Heskes
D. Kühlwein
Evgeni Tsivtsivadze
Josef Urban
LRM
82
147
0
17 Aug 2011
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