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Using Logic Programming and Kernel-Grouping for Improving
  Interpretability of Convolutional Neural Networks

Using Logic Programming and Kernel-Grouping for Improving Interpretability of Convolutional Neural Networks

19 October 2023
Parth Padalkar
Gopal Gupta
ArXivPDFHTML

Papers citing "Using Logic Programming and Kernel-Grouping for Improving Interpretability of Convolutional Neural Networks"

6 / 6 papers shown
Title
Symbolic Rule Extraction from Attention-Guided Sparse Representations in Vision Transformers
Symbolic Rule Extraction from Attention-Guided Sparse Representations in Vision Transformers
Parth Padalkar
Gopal Gupta
11
0
0
10 May 2025
CFGs: Causality Constrained Counterfactual Explanations using
  goal-directed ASP
CFGs: Causality Constrained Counterfactual Explanations using goal-directed ASP
Sopam Dasgupta
Joaquín Arias
Elmer Salazar
Gopal Gupta
13
0
0
24 May 2024
A Neurosymbolic Framework for Bias Correction in CNNs
A Neurosymbolic Framework for Bias Correction in CNNs
Parth Padalkar
Natalia Slusarz
Ekaterina Komendantskaya
Gopal Gupta
19
0
0
24 May 2024
Neuro-Symbolic Inductive Logic Programming with Logical Neural Networks
Neuro-Symbolic Inductive Logic Programming with Logical Neural Networks
Prithviraj Sen
B. W. Carvalho
Ryan Riegel
Alexander G. Gray
NAI
AI4CE
59
53
0
06 Dec 2021
Differentiable Inductive Logic Programming for Structured Examples
Differentiable Inductive Logic Programming for Structured Examples
Hikaru Shindo
Masaaki Nishino
Akihiro Yamamoto
NAI
23
29
0
02 Mar 2021
ERIC: Extracting Relations Inferred from Convolutions
ERIC: Extracting Relations Inferred from Convolutions
Joe Townsend
Theodoros Kasioumis
Hiroya Inakoshi
NAI
FAtt
8
16
0
19 Oct 2020
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