9 citations · 11 across the 2 of their papers we have counts for
6 papers
Algorithmic Bias and Data Bias: Understanding the Relation between Distributionally Robust Optimization and Data Curation
Agnieszka Słowik, Léon Bottou
Machine learning systems based on minimizing average error have been shown to perform inconsistently across notable subsets of the data, which is not exposed by a low average error…
Towards Graph Representation Learning in Emergent Communication
Agnieszka Słowik, Abhinav Gupta, William L. Hamilton +2
Recent findings in neuroscience suggest that the human brain represents information in a geometric structure (for instance, through conceptual spaces). In order to communicate, we…
Structural Inductive Biases in Emergent Communication
Agnieszka Słowik, Abhinav Gupta, William L. Hamilton +3
In order to communicate, humans flatten a complex representation of ideas and their attributes into a single word or a sentence. We investigate the impact of representation learnin…
Bayesian Optimisation with Gaussian Processes for Premise Selection
Agnieszka Słowik, Chaitanya Mangla, Mateja Jamnik +2
Heuristics in theorem provers are often parameterised. Modern theorem provers such as Vampire utilise a wide array of heuristics to control the search space explosion, thereby requ…
Spatial Graph Convolutional Networks
Tomasz Danel, Przemysław Spurek, Jacek Tabor +4
Graph Convolutional Networks (GCNs) have recently become the primary choice for learning from graph-structured data, superseding hash fingerprints in representing chemical compound…
Dilated DenseNets for Relational Reasoning
Antreas Antoniou, Agnieszka Słowik, Elliot J. Crowley +1
Despite their impressive performance in many tasks, deep neural networks often struggle at relational reasoning. This has recently been remedied with the introduction of a plug-in…