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Thermodynamics-inspired Explanations of Artificial Intelligence
v1v2v3 (latest)

Thermodynamics-inspired Explanations of Artificial Intelligence

Nature Communications (Nat Commun), 2022
27 June 2022
S. Mehdi
P. Tiwary
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Thermodynamics-inspired Explanations of Artificial Intelligence"

6 / 6 papers shown
Title
Can machines think efficiently?
Can machines think efficiently?
Adam Winchell
48
0
0
30 Oct 2025
Attention to Order: Transformers Discover Phase Transitions via Learnability
Attention to Order: Transformers Discover Phase Transitions via Learnability
Şener Özönder
84
0
0
08 Oct 2025
ZENN: A Thermodynamics-Inspired Computational Framework for Heterogeneous Data-Driven Modeling
ZENN: A Thermodynamics-Inspired Computational Framework for Heterogeneous Data-Driven Modeling
Shun Wang
S. Shang
Zi-Kui Liu
Wenrui Hao
210
0
0
14 May 2025
Sparse, Efficient and Explainable Data Attribution with DualXDA
Sparse, Efficient and Explainable Data Attribution with DualXDA
Galip Umit Yolcu
Moritz Weckbecker
Thomas Wiegand
Wojciech Samek
Sebastian Lapuschkin
TDIFAtt
291
0
0
19 Feb 2024
Enhanced Sampling with Machine Learning: A Review
Enhanced Sampling with Machine Learning: A Review
S. Mehdi
Zachary Smith
Lukas Herron
Ziyue Zou
P. Tiwary
AI4CE
163
10
0
15 Jun 2023
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
2.2K
19,394
0
16 Feb 2016
1