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On Tractable Representations of Binary Neural Networks

On Tractable Representations of Binary Neural Networks

5 April 2020
Weijia Shi
Andy Shih
Adnan Darwiche
Arthur Choi
    TPM
    OffRL
ArXivPDFHTML

Papers citing "On Tractable Representations of Binary Neural Networks"

23 / 23 papers shown
Title
Semantic Probabilistic Control of Language Models
Semantic Probabilistic Control of Language Models
Kareem Ahmed
Catarina G Belém
Padhraic Smyth
Sameer Singh
49
0
0
04 May 2025
Verifying Properties of Binary Neural Networks Using Sparse Polynomial Optimization
Verifying Properties of Binary Neural Networks Using Sparse Polynomial Optimization
Jianting Yang
Srecko Ðurasinovic
Jean B. Lasserre
Victor Magron
Jun Zhao
AAML
43
1
0
27 May 2024
Boosting-based Construction of BDDs for Linear Threshold Functions and
  Its Application to Verification of Neural Networks
Boosting-based Construction of BDDs for Linear Threshold Functions and Its Application to Verification of Neural Networks
Yiping Tang
Kohei Hatano
Eiji Takimoto
21
0
0
08 Jun 2023
Logic for Explainable AI
Logic for Explainable AI
Adnan Darwiche
40
8
0
09 May 2023
A New Class of Explanations for Classifiers with Non-Binary Features
A New Class of Explanations for Classifiers with Non-Binary Features
Chunxi Ji
Adnan Darwiche
FAtt
34
3
0
28 Apr 2023
Logic-Based Explainability in Machine Learning
Logic-Based Explainability in Machine Learning
Sasha Rubin
LRM
XAI
57
39
0
24 Oct 2022
A Scalable, Interpretable, Verifiable & Differentiable Logic Gate
  Convolutional Neural Network Architecture From Truth Tables
A Scalable, Interpretable, Verifiable & Differentiable Logic Gate Convolutional Neural Network Architecture From Truth Tables
Adrien Benamira
Tristan Guérand
Thomas Peyrin
Trevor Yap
Bryan Hooi
42
1
0
18 Aug 2022
ASTERYX : A model-Agnostic SaT-basEd appRoach for sYmbolic and
  score-based eXplanations
ASTERYX : A model-Agnostic SaT-basEd appRoach for sYmbolic and score-based eXplanations
Ryma Boumazouza
Fahima Cheikh
Bertrand Mazure
Karim Tabia
10
31
0
23 Jun 2022
On Tackling Explanation Redundancy in Decision Trees
On Tackling Explanation Redundancy in Decision Trees
Yacine Izza
Alexey Ignatiev
Sasha Rubin
FAtt
48
59
0
20 May 2022
Cardinality-Minimal Explanations for Monotonic Neural Networks
Cardinality-Minimal Explanations for Monotonic Neural Networks
Ouns El Harzli
Bernardo Cuenca Grau
Ian Horrocks
FAtt
42
5
0
19 May 2022
On the Computation of Necessary and Sufficient Explanations
On the Computation of Necessary and Sufficient Explanations
Adnan Darwiche
Chunxi Ji
FAtt
24
19
0
20 Mar 2022
Tractable Boolean and Arithmetic Circuits
Tractable Boolean and Arithmetic Circuits
Adnan Darwiche
TPM
41
12
0
07 Feb 2022
On Quantifying Literals in Boolean Logic and Its Applications to
  Explainable AI
On Quantifying Literals in Boolean Logic and Its Applications to Explainable AI
Adnan Darwiche
Pierre Marquis
17
26
0
23 Aug 2021
Explanations for Monotonic Classifiers
Explanations for Monotonic Classifiers
Sasha Rubin
Thomas Gerspacher
M. Cooper
Alexey Ignatiev
Nina Narodytska
FAtt
14
43
0
01 Jun 2021
A unified logical framework for explanations in classifier systems
A unified logical framework for explanations in classifier systems
Xinghan Liu
E. Lorini
25
12
0
30 May 2021
Probabilistic Sufficient Explanations
Probabilistic Sufficient Explanations
Eric Wang
Pasha Khosravi
Guy Van den Broeck
XAI
FAtt
TPM
30
23
0
21 May 2021
On Guaranteed Optimal Robust Explanations for NLP Models
On Guaranteed Optimal Robust Explanations for NLP Models
Emanuele La Malfa
A. Zbrzezny
Rhiannon Michelmore
Nicola Paoletti
Marta Z. Kwiatkowska
FAtt
19
47
0
08 May 2021
Declarative Approaches to Counterfactual Explanations for Classification
Declarative Approaches to Counterfactual Explanations for Classification
Leopoldo Bertossi
42
17
0
15 Nov 2020
Model Interpretability through the Lens of Computational Complexity
Model Interpretability through the Lens of Computational Complexity
Pablo Barceló
Mikaël Monet
Jorge A. Pérez
Bernardo Subercaseaux
132
94
0
23 Oct 2020
Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time
  and Delay
Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time and Delay
Sasha Rubin
Thomas Gerspacher
Martin C. Cooper
Alexey Ignatiev
Nina Narodytska
FAtt
30
59
0
13 Aug 2020
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability
Dylan Slack
Sophie Hilgard
Sameer Singh
Himabindu Lakkaraju
FAtt
29
162
0
11 Aug 2020
The Tractability of SHAP-Score-Based Explanations over Deterministic and
  Decomposable Boolean Circuits
The Tractability of SHAP-Score-Based Explanations over Deterministic and Decomposable Boolean Circuits
Marcelo Arenas
Pablo Barceló
Mikaël Monet
FAtt
41
8
0
28 Jul 2020
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
251
1,842
0
03 Feb 2017
1