PinnedMichael BronsteininTowards Data ScienceThe Road to Biology 2.0 Will Pass Through Black-Box DataFuture bio-AI breakthroughs will arise from novel high-throughput low-cost AI-specific “black-box” data modalities.·46 min read·Mar 18, 2024--1--1
Michael BronsteininTowards Data ScienceCo-operative Graph Neural NetworksA new message-passing paradigm where every node can choose to either ‘listen’, ‘broadcast’, ‘listen & broadcast’ or ‘isolate’.·11 min read·Dec 6, 2023--2--2
Michael BronsteininTowards Data ScienceTopological Generalisation with Advective Diffusion TransformersA new diffusion-based continuous GNN model offers better generalisation capabilities·9 min read·Oct 19, 2023--1--1
Michael BronsteininTowards Data ScienceDynamically rewired delayed message passing GNNsDynamic rewiring and delayed message passing mechanisms offer a tradeoff between standard MPNNs and graph Transformers·9 min read·Jun 19, 2023----
Michael BronsteininTowards Data ScienceDirection Improves Graph LearningHow a wise use of direction when doing message passing on heterophilic graphs can result in very significant gains.·10 min read·Jun 8, 2023--4--4
Michael BronsteininTowards Data ScienceHyperbolic Deep Reinforcement LearningMany RL problems have hierarchical tree-like nature. Hyperbolic geometry offers a powerful prior for such problems.·17 min read·Apr 30, 2023--5--5
Michael BronsteininTowards Data ScienceLearning Network GamesHow to learn the network underlying the interactions of players in social applications, economics, and beyond.·10 min read·Apr 20, 2023----
Michael BronsteininTowards Data ScienceGraph Neural Networks as gradient flowsGNNs derived as gradient flows minimising a learnable energy that describes attractive and repulsive forces between graph nodes.·18 min read·Oct 14, 2022--2--2
Michael BronsteininTowards Data ScienceTowards Geometric Deep Learning IV: Chemical Precursors of GNNsIn the last post in the “Towards Geometric Deep Learning” series, we look at early prototypes of GNNs in the field of chemistry.·15 min read·Jul 25, 2022--2--2
Michael BronsteininTowards Data ScienceTowards Geometric Deep Learning III: First Geometric ArchitecturesIn the third post of our series “Towards Geometric Deep Learning” we look at the first “geometric” architectures: Neocognitron and CNNs·10 min read·Jul 18, 2022----
