dais-ita interpretability-papers issues

dais-ita / interpretability-papers

Papers on interpretable deep learning, for review

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Explaining Deep Learning Models using Causal Inference

#64 pkfancy opened 6 years ago
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testing

#63 rogthlu closed 6 years ago
1
The Building Blocks of Interpretability

#62 richardtomsett opened 6 years ago
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On Fairness and Calibration

#61 richardtomsett opened 6 years ago
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On Calibration of Modern Neural Networks

#60 richardtomsett opened 6 years ago
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Theories of Deep Learning (STATS 385 course, Stanford University)

#59 richardtomsett opened 6 years ago
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Deep Learning and the Information Bottleneck Principle

#58 richardtomsett opened 6 years ago
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Why are deep nets reversible: A simple theory, with implications for training

#57 richardtomsett opened 6 years ago
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Understanding deep learning requires rethinking generalization

#56 richardtomsett opened 6 years ago
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Convolutional Neural Networks Analyzed via Convolutional Sparse Coding

#55 richardtomsett opened 6 years ago
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Deep Information Propagation

#54 richardtomsett opened 6 years ago
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Learning Functions: When Is Deep Better Than Shallow

#53 richardtomsett opened 6 years ago
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Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review

#52 richardtomsett opened 6 years ago
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Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car

#51 richardtomsett opened 6 years ago
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Rationalizing Neural Predictions

#50 richardtomsett opened 6 years ago
1
Explaining the Unexplained: A CLass-Enhanced Attentive Response (CLEAR) Approach to Understanding Deep Neural Networks

#49 richardtomsett opened 6 years ago
1
Evaluating the Visualization of What a Deep Neural Network Has Learned

#48 richardtomsett opened 6 years ago
1
Interpretable deep neural networks for single-trial EEG classification

#47 richardtomsett opened 6 years ago
1
Explaining nonlinear classification decisions with deep taylor decomposition

#46 richardtomsett opened 6 years ago
1
Layer-Wise Relevance Propagation for Deep Neural Network Architectures

#45 richardtomsett opened 6 years ago
1
Layer-wise relevance propagation for neural networks with local renormalization layers

#44 richardtomsett opened 6 years ago
1
Right for the right reasons: Training differentiable models by constraining their explanations

#43 richardtomsett opened 6 years ago
1
Streaming weak submodularity: Interpreting neural networks on the fly

#42 richardtomsett opened 6 years ago
1
Why should I trust you?: Explaining the predictions of any classifier

#41 richardtomsett opened 6 years ago
1
Show, attend and tell: Neural image caption generation with visual attention

#40 richardtomsett opened 6 years ago
1
Long-term recurrent convolutional networks for visual recognition and description

#39 richardtomsett closed 6 years ago
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Generating Visual Explanations

#38 richardtomsett opened 6 years ago
1
Opening the Black Box of Deep Neural Networks via Information

#37 richardtomsett opened 6 years ago
1
Understanding black-box predictions via influence functions

#36 richardtomsett opened 6 years ago
1
Convergent Learning: Do different neural networks learn the same representations?

#35 richardtomsett opened 6 years ago
1
Synthesizing the preferred inputs for neurons in neural networks via deep generator networks

#34 richardtomsett opened 6 years ago
1
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

#33 richardtomsett opened 6 years ago
1
Multifaceted Feature Visualization: Uncovering the Different Types of Features Learned By Each Neuron in Deep Neural Networks

#32 richardtomsett opened 6 years ago
1
Understanding Neural Networks Through Deep Visualization

#31 richardtomsett opened 6 years ago
1
Understanding Deep Image Representations by Inverting Them

#30 richardtomsett opened 6 years ago
1
Visualizing and Understanding Recurrent Networks

#29 richardtomsett opened 6 years ago
1
Adaptive deconvolutional networks for mid and high level feature learning

#28 richardtomsett closed 6 years ago
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Visualizing and Understanding Convolutional Networks

#27 richardtomsett opened 6 years ago
1
Visualizing Higher-Layer Features of a Deep Network

#26 richardtomsett opened 6 years ago
1
The Mythos of Model Interpretability

#25 richardtomsett opened 6 years ago
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A Mathematical Theory of Deep Convolutional Neural Networks for Feature Extraction

#24 richardtomsett opened 6 years ago
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Understanding Deep Convolutional Networks

#23 richardtomsett opened 6 years ago
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Lipschitz Properties for Deep Convolutional Networks

#22 richardtomsett opened 6 years ago
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Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples

#21 richardtomsett opened 6 years ago
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TreeView: Peeking into Deep Neural Networks Via Feature-Space Partitioning

#20 richardtomsett opened 6 years ago
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Provably Fair Representations

#19 richardtomsett opened 6 years ago
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Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions

#18 richardtomsett opened 6 years ago
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Human-in-the-loop Artificial Intelligence

#17 richardtomsett opened 6 years ago
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Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks

#16 richardtomsett opened 6 years ago
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The loss surface and expressivity of deep convolutional neural networks

#15 richardtomsett opened 6 years ago
0