Co-occurring keywords · papers mentioning both
Papers
A Knowledge Distillation-Based Approach to Enhance Transparency of Classifier Models
AAAI 2025
From Mechanistic Interpretability to Mechanistic Biology: Training, Evaluating, and Interpreting Sparse Autoencoders on Protein Language Models
ICML 2025
Network Inversion of Convolutional Neural Nets (Student Abstract)
AAAI 2025
Neurons to Words: A Novel Method for Automated Neural Network Interpretability and Alignment
AAAI 2025
VITAL: More Understandable Feature Visualization through Distribution Alignment and Relevant Information Flow
ICCV 2025
Adversarial Attacks on the Interpretation of Neuron Activation Maximization
AAAI 2024
Don’t trust your eyes: on the (un)reliability of feature visualizations
ICML 2024
Parallel Backpropagation for Shared-Feature Visualization
NeurIPS 2024
Team MLab at SemEval-2024 Task 8: Analyzing Encoder Embeddings for Detecting LLM-generated Text
SemEval 2024
A Study on Visualization of Voiceprint Feature
Interspeech 2023
Unlocking Feature Visualization for Deep Network with MAgnitude Constrained Optimization
NeurIPS 2023
B-Cos Networks: Alignment Is All We Need for Interpretability
CVPR 2022
InterpretDL: Explaining Deep Models in PaddlePaddle
JMLR 2022
A Framework to Learn with Interpretation
NeurIPS 2021
CAMERAS: Enhanced Resolution and Sanity Preserving Class Activation Mapping for Image Saliency
CVPR 2021
Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization
ICLR 2021
How Well do Feature Visualizations Support Causal Understanding of CNN Activations?
NeurIPS 2021
Rotation-Invariant Gait Identification with Quaternion Convolutional Neural Networks (Student Abstract)
AAAI 2021
Attack to Explain Deep Representation
CVPR 2020
Visualizing Deep Networks by Optimizing with Integrated Gradients
AAAI 2020
Feature Space Visualization with Spatial Similarity Maps for Pathological Speech Data
Interspeech 2019
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
ICLR 2019
NeuroX: A Toolkit for Analyzing Individual Neurons in Neural Networks
AAAI 2019
Understanding and Visualizing Deep Visual Saliency Models
CVPR 2019
Understanding Deep Networks via Extremal Perturbations and Smooth Masks
ICCV 2019