2 citations · 6 across the 5 of their papers we have counts for
5 papers
Neural Embeddings for Protein Graphs
Francesco Ceccarelli, Lorenzo Giusti, Sean B. Holden +1
Proteins perform much of the work in living organisms, and consequently the development of efficient computational methods for protein representation is essential for advancing lar…
Building a 3-Player Mahjong AI using Deep Reinforcement Learning
Xiangyu Zhao, Sean B. Holden
Mahjong is a popular multi-player imperfect-information game developed in China in the late 19th-century, with some very challenging features for AI research. Sanma, being a 3-play…
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…