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06/21/2022
Automatic Concept Extraction for Concept Bottleneck-based Video Classification
Recent efforts in interpretable deep learning models have shown that con...
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10/15/2021
Using DeepProbLog to perform Complex Event Processing on an Audio Stream
In this paper, we present an approach to Complex Event Processing (CEP) ...
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12/09/2020
NSL: Hybrid Interpretable Learning From Noisy Raw Data
Inductive Logic Programming (ILP) systems learn generalised, interpretab...
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11/20/2020
A General Framework for Distributed Inference with Uncertain Models
This paper studies the problem of distributed classification with a netw...
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09/07/2020
A Hybrid Neuro-Symbolic Approach for Complex Event Processing
Training a model to detect patterns of interrelated events that form sit...
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06/07/2020
Uncertainty-Aware Deep Classifiers using Generative Models
Deep neural networks are often ignorant about what they do not know and ...
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11/04/2019
Spherical Text Embedding
Unsupervised text embedding has shown great power in a wide range of NLP...
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10/24/2019
Non-Bayesian Social Learning with Gaussian Uncertain Models
Non-Bayesian social learning theory provides a framework for distributed...
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10/15/2019
Quantifying Classification Uncertainty using Regularized Evidential Neural Networks
Traditional deep neural nets (NNs) have shown the state-of-the-art perfo...
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09/10/2019
Non-Bayesian Social Learning with Uncertain Models over Time-Varying Directed Graphs
We study the problem of non-Bayesian social learning with uncertain mode...
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09/09/2019
Non-Bayesian Social Learning with Uncertain Models
Non-Bayesian social learning theory provides a framework that models dis...
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07/05/2019
Prior Activation Distribution (PAD): A Versatile Representation to Utilize DNN Hidden Units
In this paper, we introduce the concept of Prior Activation Distribution...
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09/20/2018
Probabilistic Logic Programming with Beta-Distributed Random Variables
We enable aProbLog---a probabilistic logical programming approach---to r...
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09/20/2018
Uncertainty Aware AI ML: Why and How
This paper argues the need for research to realize uncertainty-aware art...
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06/05/2018
Evidential Deep Learning to Quantify Classification Uncertainty
Deterministic neural nets have been shown to learn effective predictors ...
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03/05/2018