New preprint: how many patients could we save with LLM priors? Exploring the effect of eliciting informative priors for Bayesian clinical trials. arxiv.org/abs/2509.04250

📊📉📈 Better data visualizations with AI: can LLMs provide constructive critiques on existing charts? We explore how generative AI can automate #MakeoverMonday -type exercises, suggesting improvements to existing charts.

📄 New preprint + benchmark dataset 💽

arxiv.org/abs/2508.05637

🧬BioDisco, an open-source biomedical hypothesis generator, uses agentic LLMs, knowledge graphs and literature search, with an iterative self-evaluation loop to discover novel relations, significantly outperforming other architectures.

Preprint: arxiv.org/abs/2508.01285

New: unofficial @quarto.org template for the upcoming @realaaai.bsky.social 2026 conference. Write your submission in Markdown with reproducible, inline computations!

github.com/Selbosh/aaai...

What is a "Visible Neural Network"? It's a new kind of deep learning model for multi-omics, where prior knowledge and interpretability are baked into the architecture.

📄 We reviewed dozens of models, datasets & applications, and call for better tools/benchmarks:

www.frontiersin.org/journals/art...

Health Research From Home Hackathon 2025 |
This hackathon is being held by Health Research From Home Partnership led by the @OfficialUoM. Register your interest now: health-research-from-home.github.io/DataAnalysis...

Just published: 'Had enough of experts? Quantitative retrieval from large language models'

Can LLMs, having read the scientific literature, offer us useful numerical info to help fill in missing data and fit statistical models, like a real human expert? We investigate:

doi.org/10.1002/sta4...

New blog post: on all the English I have had to learn since moving to Germany 🇬🇧 🇩🇪

selbydavid.com/2025/03/13/d...

New blog post: Alternatives to @overleaf.com for #rstats, reproducible writing and collaboration

selbydavid.com/2025/03/04/o...

New online! Beyond the black box with biologically informed neural networks

Thrilled to share our latest publication in @natrevgenet.bsky.social. We explore how deep learning models infused with prior knowledge—biologically-informed neural networks or BINNs—offer better predictive accuracy and interpretability in multi-omics data analysis. www.nature.com/articles/s41...

Paper just accepted in Stat!

Can LLMs replace experts as sources of numerical information, such as Bayesian prior distributions for statistical models, or filling in missing values in tabular datasets for ML tasks?

We evaluate on applications across different fields.

arxiv.org/abs/2402.07770

How might one redesign this data visualization to avoid using much-maligned 'plunger plots'?

#visualisation

From www.nature.com/articles/s41...

Pleased to present our poster at #NeurIPS2024 workshop on Bayesian Decisionmaking and Uncertainty! 🎉 Our work explores using large language models for eliciting expert-informed Bayesian priors. Elicited lots of discussion with the ML community too! Check it out: neurips.cc/virtual/2024...

Excited to share our new preprint: Visible neural networks for multi-omics integration: a critical review! 🌟 We systematically analyse 86 studies on biologically informed neural networks (BINNs/VNNs), highlighting trends, challenges, interesting ideas & opportunities. www.biorxiv.org/content/10.1...