290 citations · 469 across the 35 of their papers we have counts for
11 papers · 1 filter
bLIMEy: Surrogate Prediction Explanations Beyond LIME
Kacper Sokol, Alexander Hepburn, Raul Santos-Rodriguez +1
Surrogate explainers of black-box machine learning predictions are of paramount importance in the field of eXplainable Artificial Intelligence since they can be applied to any type…
PerceptNet: A Human Visual System Inspired Neural Network for Estimating Perceptual Distance
Alexander Hepburn, Valero Laparra, Jesús Malo +2
Traditionally, the vision community has devised algorithms to estimate the distance between an original image and images that have been subject to perturbations. Inspiration was us…
FACE: Feasible and Actionable Counterfactual Explanations
Rafael Poyiadzi, Kacper Sokol, Raul Santos-Rodriguez +2
Work in Counterfactual Explanations tends to focus on the principle of "the closest possible world" that identifies small changes leading to the desired outcome. In this paper we a…
FAT Forensics: A Python Toolbox for Algorithmic Fairness, Accountability and Transparency
Kacper Sokol, Raul Santos-Rodriguez, Peter Flach
Today, artificial intelligence systems driven by machine learning algorithms can be in a position to take important, and sometimes legally binding, decisions about our everyday liv…
Online Feature Selection for Activity Recognition using Reinforcement Learning with Multiple Feedback
Taku Yamagata, Raúl Santos-Rodríguez, Ryan McConville +1
Recent advances in both machine learning and Internet-of-Things have attracted attention to automatic Activity Recognition, where users wear a device with sensors and their outputs…
N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding
Ryan McConville, Raul Santos-Rodriguez, Robert J Piechocki +1
Deep clustering has increasingly been demonstrating superiority over conventional shallow clustering algorithms. Deep clustering algorithms usually combine representation learning…
Enforcing Perceptual Consistency on Generative Adversarial Networks by Using the Normalised Laplacian Pyramid Distance
Alexander Hepburn, Valero Laparra, Ryan McConville +1
In recent years there has been a growing interest in image generation through deep learning. While an important part of the evaluation of the generated images usually involves visu…
Location Anomalies Detection for Connected and Autonomous Vehicles
Xiaoyang Wang, Ioannis Mavromatis, Andrea Tassi +2
Future Connected and Automated Vehicles (CAV), and more generally ITS, will form a highly interconnected system. Such a paradigm is referred to as the Internet of Vehicles (herein…
Ordinal Regression as Structured Classification
Niall Twomey, Rafael Poyiadzi, Callum Mann +1
This paper extends the class of ordinal regression models with a structured interpretation of the problem by applying a novel treatment of encoded labels. The net effect of this is…
Conditional t-SNE: Complementary t-SNE embeddings through factoring out prior information
Bo Kang, Darío García García, Jefrey Lijffijt +2
Dimensionality reduction and manifold learning methods such as t-Distributed Stochastic Neighbor Embedding (t-SNE) are routinely used to map high-dimensional data into a 2-dimensio…
Neural ODEs with stochastic vector field mixtures
Niall Twomey, Michał Kozłowski, Raúl Santos-Rodríguez
It was recently shown that neural ordinary differential equation models cannot solve fundamental and seemingly straightforward tasks even with high-capacity vector field representa…