Explaining and Interpreting LSTMs

25 September 2019

L. Arras

Jose A. Arjona-Medina

Papers citing "Explaining and Interpreting LSTMs"

30 / 30 papers shown

Title
A Close Look at Decomposition-based XAI-Methods for Transformer Language Models L. Arras Bruno Puri Patrick Kahardipraja Sebastian Lapuschkin Wojciech Samek 35 0 0 21 Feb 2025
Recent Advances in Malware Detection: Graph Learning and Explainability Hossein Shokouhinejad Roozbeh Razavi-Far Hesamodin Mohammadian Mahdi Rabbani Samuel Ansong Griffin Higgins Ali Ghorbani AAML 68 2 0 14 Feb 2025
Towards Symbolic XAI -- Explanation Through Human Understandable Logical Relationships Between Features Thomas Schnake Farnoush Rezaei Jafaria Jonas Lederer Ping Xiong Shinichi Nakajima Stefan Gugler G. Montavon Klaus-Robert Müller 34 3 0 30 Aug 2024
The Clever Hans Effect in Unsupervised Learning Jacob R. Kauffmann Jonas Dippel Lukas Ruff Wojciech Samek Klaus-Robert Müller G. Montavon SSL CML HAI 24 1 0 15 Aug 2024
Machine-Learned Closure of URANS for Stably Stratified Turbulence: Connecting Physical Timescales & Data Hyperparameters of Deep Time-Series Models Muralikrishnan Gopalakrishnan Meena Demetri Liousas Andrew D. Simin Aditya Kashi Wesley Brewer James J. Riley S. D. B. Kops AI4TS AI4CE 36 1 0 24 Apr 2024
The benefits and costs of explainable artificial intelligence in visual quality control: Evidence from fault detection performance and eye movements Romy Müller David F. Reindel Yannick D. Stadtfeld 6 4 0 02 Oct 2023
GAMER-MRIL identifies Disability-Related Brain Changes in Multiple Sclerosis Po-Jui Lu Benjamin Odry M. Barakovic Matthias Weigel Robin Sandkühler ... Mario Ocampo Pineda J. Kuhle L. Kappos Philippe C. Cattin C. Granziera 17 0 0 15 Aug 2023
Unlocking Layer-wise Relevance Propagation for Autoencoders Kenyu Kobayashi Renata Khasanova Arno Schneuwly Felix Schmidt Matteo Casserini FAtt 8 0 0 21 Mar 2023
Machine Learning based prediction of Glucose Levels in Type 1 Diabetes Patients with the use of Continuous Glucose Monitoring Data Jakub J Dylag 11 0 0 24 Feb 2023
Disentangled Explanations of Neural Network Predictions by Finding Relevant Subspaces Pattarawat Chormai J. Herrmann Klaus-Robert Muller G. Montavon FAtt 43 17 0 30 Dec 2022
On the Explainability of Natural Language Processing Deep Models Julia El Zini M. Awad 25 82 0 13 Oct 2022
Implicit N-grams Induced by Recurrence Xiaobing Sun Wei Lu 11 3 0 05 May 2022
Explainable Online Lane Change Predictions on a Digital Twin with a Layer Normalized LSTM and Layer-wise Relevance Propagation C. Wehner Francis Powlesland Bashar Altakrouri Ute Schmid FAtt 22 8 0 04 Apr 2022
NeuroView-RNN: It's About Time C. Barberan Sina Alemohammad Naiming Liu Randall Balestriero Richard G. Baraniuk AI4TS HAI 33 2 0 23 Feb 2022
XAI for Transformers: Better Explanations through Conservative Propagation Ameen Ali Thomas Schnake Oliver Eberle G. Montavon Klaus-Robert Muller Lior Wolf FAtt 12 86 0 15 Feb 2022
Learning Temporal Rules from Noisy Timeseries Data Karan Samel Zelin Zhao Binghong Chen Shuang Li D. Subramanian Irfan Essa Le Song NoLa NAI AI4TS AI4CE 15 2 0 11 Feb 2022
Toward Explainable AI for Regression Models S. Letzgus Patrick Wagner Jonas Lederer Wojciech Samek Klaus-Robert Muller G. Montavon XAI 22 63 0 21 Dec 2021
Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy Christopher J. Anders David Neumann Wojciech Samek K. Müller Sebastian Lapuschkin 14 62 0 24 Jun 2021
Detection of Dataset Shifts in Learning-Enabled Cyber-Physical Systems using Variational Autoencoder for Regression Feiyang Cai A. Ozdagli X. Koutsoukos 21 2 0 14 Apr 2021
XNAP: Making LSTM-based Next Activity Predictions Explainable by Using LRP Sven Weinzierl Sandra Zilker Jens Brunk K. Revoredo Martin Matzner J. Becker 9 26 0 18 Aug 2020
Modern Hopfield Networks and Attention for Immune Repertoire Classification Michael Widrich Bernhard Schafl Hubert Ramsauer Milena Pavlović Lukas Gruber ... Johannes Brandstetter G. K. Sandve Victor Greiff Sepp Hochreiter G. Klambauer 179 117 0 16 Jul 2020
Human Trajectory Forecasting in Crowds: A Deep Learning Perspective Parth Kothari S. Kreiss Alexandre Alahi HAI AI4TS 14 236 0 07 Jul 2020
Higher-Order Explanations of Graph Neural Networks via Relevant Walks Thomas Schnake Oliver Eberle Jonas Lederer Shinichi Nakajima Kristof T. Schütt Klaus-Robert Muller G. Montavon 8 212 0 05 Jun 2020
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications Wojciech Samek G. Montavon Sebastian Lapuschkin Christopher J. Anders K. Müller XAI 24 82 0 17 Mar 2020
Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI L. Arras Ahmed Osman Wojciech Samek XAI AAML 16 148 0 16 Mar 2020
Physically Interpretable Neural Networks for the Geosciences: Applications to Earth System Variability B. Toms E. Barnes I. Ebert‐Uphoff AI4CE 10 210 0 04 Dec 2019
Towards Explainable Artificial Intelligence Wojciech Samek K. Müller XAI 14 433 0 26 Sep 2019
From Clustering to Cluster Explanations via Neural Networks Jacob R. Kauffmann Malte Esders Lukas Ruff G. Montavon Wojciech Samek K. Müller 9 68 0 18 Jun 2019
RUDDER: Return Decomposition for Delayed Rewards Jose A. Arjona-Medina Michael Gillhofer Michael Widrich Thomas Unterthiner Johannes Brandstetter Sepp Hochreiter 11 211 0 20 Jun 2018
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,233 0 24 Jun 2017