HOME > 상세정보

상세정보

Explainable AI : interpreting, explaining and visualizing deep learning

Explainable AI : interpreting, explaining and visualizing deep learning (8회 대출)

자료유형
단행본
개인저자
Samek, Wojciech.
서명 / 저자사항
Explainable AI : interpreting, explaining and visualizing deep learning / Wojciech Samek ... [et al.], (eds.).
발행사항
Cham :   Springer,   c2019.  
형태사항
xi, 438 p. : ill. (chiefly col.) ; 24 cm.
총서사항
Lecture notes in artificia intellligence,0302-9743 ; 11700
ISBN
9783030289539 (pbk.) 9783030289546 (ebk.)
서지주기
Includes bibliographical references and index.
000 00000nam u2200205 a 4500
001 000046001992
005 20191217095354
008 191011s2019 sz a b 001 0 eng d
020 ▼a 9783030289539 (pbk.)
020 ▼a 9783030289546 (ebk.)
040 ▼a 211009 ▼c 211009 ▼d 211009
082 0 4 ▼a 006.3 ▼2 23
084 ▼a 006.3 ▼2 DDCK
090 ▼a 006.3 ▼b E96
245 0 0 ▼a Explainable AI : ▼b interpreting, explaining and visualizing deep learning / ▼c Wojciech Samek ... [et al.], (eds.).
260 ▼a Cham : ▼b Springer, ▼c c2019.
300 ▼a xi, 438 p. : ▼b ill. (chiefly col.) ; ▼c 24 cm.
490 1 ▼a Lecture notes in artificia intellligence, ▼x 0302-9743 ; ▼v 11700
490 1 ▼a Lecture notes in computer science
504 ▼a Includes bibliographical references and index.
700 1 ▼a Samek, Wojciech.
830 0 ▼a Lecture notes in artificia intellligence ; ▼v 11700.
830 0 ▼a Lecture notes in computer science.
945 ▼a KLPA

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 과학도서관/Sci-Info(2층서고)/ 청구기호 006.3 E96 등록번호 121250609 도서상태 대출가능 반납예정일 예약 서비스 B M
No. 2 소장처 과학도서관/Sci-Info(2층서고)/ 청구기호 006.3 E96 등록번호 121251524 도서상태 대출가능 반납예정일 예약 서비스 B M

컨텐츠정보

목차

Towards Explainable Artificial Intelligence -- Transparency: Motivations and Challenges -- Interpretability in Intelligent Systems: A New Concept? -- Understanding Neural Networks via Feature Visualization: A Survey -- Interpretable Text-to-Image Synthesis with Hierarchical Semantic Layout Generation -- Unsupervised Discrete Representation Learning -- Towards Reverse-Engineering Black-Box Neural Networks -- Explanations for Attributing Deep Neural Network Predictions -- Gradient-Based Attribution Methods -- Layer-Wise Relevance Propagation: An Overview -- Explaining and Interpreting LSTMs -- Comparing the Interpretability of Deep Networks via Network Dissection -- Gradient-Based vs. Propagation-Based Explanations: An Axiomatic Comparison -- The (Un)reliability of Saliency Methods -- Visual Scene Understanding for Autonomous Driving Using Semantic Segmentation -- Understanding Patch-Based Learning of Video Data by Explaining Predictions -- Quantum-Chemical Insights from Interpretable Atomistic Neural Networks -- Interpretable Deep Learning in Drug Discovery -- Neural Hydrology: Interpreting LSTMs in Hydrology -- Feature Fallacy: Complications with Interpreting Linear Decoding Weights in fMRI -- Current Advances in Neural Decoding -- Software and Application Patterns for Explanation Methods.

관련분야 신착자료

Deisenroth, Marc Peter (2020)