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Striving for Simplicity: The All Convolutional Net
v1v2v3 (latest)

Striving for Simplicity: The All Convolutional Net

International Conference on Learning Representations (ICLR), 2014
21 December 2014
Jost Tobias Springenberg
Alexey Dosovitskiy
Thomas Brox
Martin Riedmiller
    FAtt
ArXiv (abs)PDFHTML

Papers citing "Striving for Simplicity: The All Convolutional Net"

50 / 1,916 papers shown
AI for the prediction of early stages of Alzheimer's disease from
  neuroimaging biomarkers -- A narrative review of a growing field
AI for the prediction of early stages of Alzheimer's disease from neuroimaging biomarkers -- A narrative review of a growing field
Thorsten Rudroff
O. Rainio
R. Klén
237
21
0
25 Jun 2024
Machine Learning Techniques in Automatic Music Transcription: A
  Systematic Survey
Machine Learning Techniques in Automatic Music Transcription: A Systematic Survey
Fatemeh Jamshidi
Gary Pike
Amit Das
Richard Chapman
176
8
0
20 Jun 2024
Latent Functional Maps: a spectral framework for representation alignment
Latent Functional Maps: a spectral framework for representation alignment
Marco Fumero
Marco Pegoraro
Valentino Maiorca
Francesco Locatello
Emanuele Rodolà
510
1
0
20 Jun 2024
Explaning with trees: interpreting CNNs using hierarchies
Explaning with trees: interpreting CNNs using hierarchies
Caroline Mazini Rodrigues
Nicolas Boutry
Laurent Najman
162
0
0
19 Jun 2024
On the Feasibility of Fidelity$^-$ for Graph Pruning
On the Feasibility of Fidelity−^-− for Graph Pruning
Yong-Min Shin
Won-Yong Shin
168
1
0
17 Jun 2024
GECOBench: A Gender-Controlled Text Dataset and Benchmark for Quantifying Biases in Explanations
GECOBench: A Gender-Controlled Text Dataset and Benchmark for Quantifying Biases in Explanations
Rick Wilming
Artur Dox
Hjalmar Schulz
Marta Oliveira
Benedict Clark
Stefan Haufe
267
3
0
17 Jun 2024
Don't Forget Too Much: Towards Machine Unlearning on Feature Level
Don't Forget Too Much: Towards Machine Unlearning on Feature Level
Heng Xu
Tianqing Zhu
Wanlei Zhou
Wei Zhao
MU
205
7
0
16 Jun 2024
IG2: Integrated Gradient on Iterative Gradient Path for Feature
  Attribution
IG2: Integrated Gradient on Iterative Gradient Path for Feature Attribution
Yue Zhuo
Zhiqiang Ge
273
17
0
16 Jun 2024
Phoneme Discretized Saliency Maps for Explainable Detection of
  AI-Generated Voice
Phoneme Discretized Saliency Maps for Explainable Detection of AI-Generated VoiceInterspeech (Interspeech), 2024
Shubham Gupta
Mirco Ravanelli
Pascal Germain
Cem Subakan
FAtt
206
4
0
14 Jun 2024
Challenges in explaining deep learning models for data with biological
  variation
Challenges in explaining deep learning models for data with biological variationPLoS ONE (PLoS ONE), 2024
Lenka Tětková
E. Dreier
Robin Malm
Lars Kai Hansen
AAML
224
1
0
14 Jun 2024
Applications of Explainable artificial intelligence in Earth system
  science
Applications of Explainable artificial intelligence in Earth system science
Feini Huang
Shijie Jiang
Lu Li
Yongkun Zhang
Ye Zhang
Ruqing Zhang
Qingliang Li
Danxi Li
Wei Shangguan
Yongjiu Dai
224
6
0
12 Jun 2024
GENIU: A Restricted Data Access Unlearning for Imbalanced Data
GENIU: A Restricted Data Access Unlearning for Imbalanced Data
Chenhao Zhang
Shaofei Shen
Yawen Zhao
Weitong Tony Chen
Miao Xu
MU
175
6
0
12 Jun 2024
Graphical Perception of Saliency-based Model Explanations
Graphical Perception of Saliency-based Model Explanations
Yayan Zhao
Mingwei Li
Matthew Berger
XAIFAtt
319
2
0
11 Jun 2024
FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model for
  Classification of Mass Margins in Digital Mammography
FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model for Classification of Mass Margins in Digital Mammography
Julia Yang
Alina Jade Barnett
Jon Donnelly
Satvik Kishore
Jerry Fang
F. Schwartz
Chaofan Chen
Joseph Y. Lo
Cynthia Rudin
MedIm
188
1
0
10 Jun 2024
Attri-Net: A Globally and Locally Inherently Interpretable Model for Multi-Label Classification Using Class-Specific Counterfactuals
Attri-Net: A Globally and Locally Inherently Interpretable Model for Multi-Label Classification Using Class-Specific CounterfactualsMachine Learning for Biomedical Imaging (MLBI), 2024
Susu Sun
S. Woerner
Andreas Maier
Lisa M. Koch
Christian F. Baumgartner
FAtt
319
2
0
08 Jun 2024
Provably Better Explanations with Optimized Aggregation of Feature
  Attributions
Provably Better Explanations with Optimized Aggregation of Feature AttributionsInternational Conference on Machine Learning (ICML), 2024
Thomas Decker
Ananta R. Bhattarai
Jindong Gu
Volker Tresp
Florian Buettner
214
6
0
07 Jun 2024
Leveraging Activations for Superpixel Explanations
Leveraging Activations for Superpixel Explanations
Ahcène Boubekki
Samuel G. Fadel
Sebastian Mair
AAMLFAttXAI
225
0
0
07 Jun 2024
Revisiting Scalable Hessian Diagonal Approximations for Applications in
  Reinforcement Learning
Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning
Mohamed Elsayed
Homayoon Farrahi
Felix Dangel
A. Rupam Mahmood
380
6
0
05 Jun 2024
Tensor Polynomial Additive Model
Tensor Polynomial Additive Model
Yang Chen
Ce Zhu
Jiani Liu
Yipeng Liu
TPM
182
0
0
05 Jun 2024
Enhancing predictive imaging biomarker discovery through treatment
  effect analysis
Enhancing predictive imaging biomarker discovery through treatment effect analysis
Shuhan Xiao
Lukas Klein
Jens Petersen
Philipp Vollmuth
Paul F. Jaeger
Klaus H. Maier-Hein
188
1
0
04 Jun 2024
Explainable Deep Learning Analysis for Raga Identification in Indian Art
  Music
Explainable Deep Learning Analysis for Raga Identification in Indian Art Music
Parampreet Singh
Vipul Arora
113
7
0
04 Jun 2024
Expected Grad-CAM: Towards gradient faithfulness
Expected Grad-CAM: Towards gradient faithfulness
Vincenzo Buono
Peyman Sheikholharam Mashhadi
M. Rahat
Prayag Tiwari
Stefan Byttner
FAtt
264
3
0
03 Jun 2024
VOICE: Variance of Induced Contrastive Explanations to quantify
  Uncertainty in Neural Network Interpretability
VOICE: Variance of Induced Contrastive Explanations to quantify Uncertainty in Neural Network Interpretability
Mohit Prabhushankar
Ghassan AlRegib
FAttUQCV
176
3
0
01 Jun 2024
Length-scale study in deep learning prediction for non-small cell lung
  cancer brain metastasis
Length-scale study in deep learning prediction for non-small cell lung cancer brain metastasis
Haowen Zhou
Steven
S. Lin
Mark Watson
Cory T. Bernadt
Oumeng Zhang
R. Govindan
R. Cote
Changhuei Yang
173
2
0
01 Jun 2024
CONFINE: Conformal Prediction for Interpretable Neural Networks
CONFINE: Conformal Prediction for Interpretable Neural Networks
Linhui Huang
S. Lala
N. Jha
522
5
0
01 Jun 2024
einspace: Searching for Neural Architectures from Fundamental Operations
einspace: Searching for Neural Architectures from Fundamental Operations
Linus Ericsson
Miguel Espinosa
Chenhongyi Yang
Antreas Antoniou
Amos Storkey
Shay B. Cohen
Jingyu Sun
Elliot J. Crowley
255
4
0
31 May 2024
Applications of interpretable deep learning in neuroimaging: a
  comprehensive review
Applications of interpretable deep learning in neuroimaging: a comprehensive review
Lindsay Munroe
Mariana da Silva
Faezeh Heidari
I. Grigorescu
Simon Dahan
E. C. Robinson
Maria Deprez
Po-Wah So
AI4CE
222
14
0
30 May 2024
Recurrent and Convolutional Neural Networks in Classification of EEG
  Signal for Guided Imagery and Mental Workload Detection
Recurrent and Convolutional Neural Networks in Classification of EEG Signal for Guided Imagery and Mental Workload Detection
Filip Postepski
Grzegorz M. Wójcik
Krzysztof Wróbel
Andrzej Kawiak
Katarzyna Zemla
Grzegorz Sedek
58
10
0
27 May 2024
Exploring the Relationship Between Feature Attribution Methods and Model
  Performance
Exploring the Relationship Between Feature Attribution Methods and Model Performance
Priscylla Silva
Claudio T. Silva
L. G. Nonato
FAtt
129
8
0
22 May 2024
Part-based Quantitative Analysis for Heatmaps
Part-based Quantitative Analysis for Heatmaps
Osman Tursun
Sinan Kalkan
Akila Pemasiri
Sridha Sridharan
Clinton Fookes
257
0
0
22 May 2024
Fully Exploiting Every Real Sample: SuperPixel Sample Gradient Model
  Stealing
Fully Exploiting Every Real Sample: SuperPixel Sample Gradient Model StealingComputer Vision and Pattern Recognition (CVPR), 2024
Yunlong Zhao
Xiaoheng Deng
Yijing Liu
Xin-jun Pei
Jiazhi Xia
Wei Chen
AAML
248
4
0
18 May 2024
Parallel Backpropagation for Shared-Feature Visualization
Parallel Backpropagation for Shared-Feature VisualizationNeural Information Processing Systems (NeurIPS), 2024
Alexander Lappe
Anna Bognár
Ghazaleh Ghamkhari Nejad
A. Mukovskiy
Lucas M. Martini
Martin A. Giese
Rufin Vogels
FAtt
161
1
0
16 May 2024
Manifold Integrated Gradients: Riemannian Geometry for Feature
  Attribution
Manifold Integrated Gradients: Riemannian Geometry for Feature AttributionInternational Conference on Machine Learning (ICML), 2024
Eslam Zaher
Maciej Trzaskowski
Quan Nguyen
Fred Roosta
AAML
258
8
0
16 May 2024
Solving the enigma: Enhancing faithfulness and comprehensibility in explanations of deep networks
Solving the enigma: Enhancing faithfulness and comprehensibility in explanations of deep networksAI Open (AO), 2024
Michail Mamalakis
Antonios Mamalakis
Ingrid Agartz
L. Morch-Johnsen
Graham K Murray
J. Suckling
Pietro Lio
506
1
0
16 May 2024
SMUG-Explain: A Framework for Symbolic Music Graph Explanations
SMUG-Explain: A Framework for Symbolic Music Graph Explanations
E. Karystinaios
Francesco Foscarin
Gerhard Widmer
275
2
0
15 May 2024
Deep Learning in Earthquake Engineering: A Comprehensive Review
Deep Learning in Earthquake Engineering: A Comprehensive Review
Yazhou Xie
AI4CE
162
11
0
15 May 2024
Towards a Novel Measure of User Trust in XAI Systems
Towards a Novel Measure of User Trust in XAI Systems
Miquel Miró-Nicolau
Gabriel Moyà Alcover
Antoni Jaume-i-Capó
Manuel González Hidalgo
Adel Ghazel
Maria Gemma Sempere Campello
Juan Antonio Palmer Sancho
297
0
0
09 May 2024
A Fresh Look at Sanity Checks for Saliency Maps
A Fresh Look at Sanity Checks for Saliency Maps
Anna Hedström
Leander Weber
Sebastian Lapuschkin
Marina M.-C. Höhne
FAttLRM
309
13
0
03 May 2024
Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and
  Beyond: A Survey
Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A SurveyICT express (IE), 2024
Rokas Gipiškis
Chun-Wei Tsai
Olga Kurasova
333
30
0
02 May 2024
Towards Optimising EEG Decoding using Post-hoc Explanations and Domain
  Knowledge
Towards Optimising EEG Decoding using Post-hoc Explanations and Domain KnowledgeAnnual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2024
Param S. Rajpura
Y. Meena
256
1
0
02 May 2024
A Backdoor-based Explainable AI Benchmark for High Fidelity Evaluation of Attributions
A Backdoor-based Explainable AI Benchmark for High Fidelity Evaluation of Attributions
Peiyu Yang
Naveed Akhtar
Jiantong Jiang
Lin Wang
XAI
225
2
0
02 May 2024
Reliable or Deceptive? Investigating Gated Features for Smooth Visual
  Explanations in CNNs
Reliable or Deceptive? Investigating Gated Features for Smooth Visual Explanations in CNNs
Soham Mitra
Atri Sukul
Swalpa Kumar Roy
Pravendra Singh
Vinay Kumar Verma
AAMLFAtt
174
1
0
30 Apr 2024
Rad4XCNN: a new agnostic method for post-hoc global explanation of CNN-derived features by means of radiomics
Rad4XCNN: a new agnostic method for post-hoc global explanation of CNN-derived features by means of radiomics
Francesco Prinzi
C. Militello
Calogero Zarcaro
T. Bartolotta
Salvatore Gaglio
Salvatore Vitabile
190
5
0
26 Apr 2024
A Learning Paradigm for Interpretable Gradients
A Learning Paradigm for Interpretable Gradients
Felipe Figueroa
Hanwei Zhang
R. Sicre
Yannis Avrithis
Stéphane Ayache
FAtt
189
0
0
23 Apr 2024
CA-Stream: Attention-based pooling for interpretable image recognition
CA-Stream: Attention-based pooling for interpretable image recognition
Felipe Torres
Hanwei Zhang
R. Sicre
Stéphane Ayache
Yannis Avrithis
253
2
0
23 Apr 2024
Guided AbsoluteGrad: Magnitude of Gradients Matters to Explanation's Localization and Saliency
Guided AbsoluteGrad: Magnitude of Gradients Matters to Explanation's Localization and Saliency
Jun Huang
Yan Liu
FAtt
312
1
0
23 Apr 2024
Integrated Gradient Correlation: a Dataset-wise Attribution Method
Integrated Gradient Correlation: a Dataset-wise Attribution Method
Pierre Lelievre
Chien-Chung Chen
142
0
0
22 Apr 2024
Machine Unlearning via Null Space Calibration
Machine Unlearning via Null Space Calibration
Huiqiang Chen
Tianqing Zhu
Xin Yu
Wanlei Zhou
267
20
0
21 Apr 2024
Toward Understanding the Disagreement Problem in Neural Network Feature
  Attribution
Toward Understanding the Disagreement Problem in Neural Network Feature Attribution
Niklas Koenen
Marvin N. Wright
FAtt
196
11
0
17 Apr 2024
CNN-based explanation ensembling for dataset, representation and
  explanations evaluation
CNN-based explanation ensembling for dataset, representation and explanations evaluation
Weronika Hryniewska-Guzik
Luca Longo
P. Biecek
FAtt
205
2
0
16 Apr 2024
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