Final deadline reminder: applications to AAE close today. Join us at Gatsby for two days on adaptive experimentation, causal inference, bandits, RL, and sequential decision-making. Apply: aae-workshop.github.io/info/

Speaker spotlight #5: Ian Waudby-Smith, UC Berkeley. Can we perform sequential hypothesis testing while adaptively choosing which arm to sample? Ian will discuss recent work on multi-armed sequential testing by betting.

Only 2 days left to apply to the Advances in Adaptive Experimentation Workshop. Low regret action: submit before May 28. 📅 June 18–19 📍 Gatsby Computational Neuroscience Unit, London 🔗 aae-workshop.github.io/info/

Only 3 days left to submit your application / poster abstract for AAE at Gatsby. Deadline: May 28 Apply: aae-workshop.github.io/info/

Speaker spotlight #5: Koulik Khamaru, Rutgers University. Can regularization make contextual bandits more stable? Koulik will present Stabilizing Bandit Algorithms via Regularization, on adaptive algorithms that combine low regret with reliable statistical inference.

Speaker spotlight #4: Gergely Neu, ICREA & UPF. Can stochastic control offer a new route to generative modeling? Gergely will present Value-Driven Transport, a stochastic-control approach to generative modeling via efficient sample transport.

Only 6 days left to apply for the Advances in Adaptive Experimentation Workshop! 📅 June 18–19 📍 Gatsby Computational Neuroscience Unit, London Two days on causal inference, adaptive experiments, bandits, and RL. Apply here: t.co/Zar0qWhgA8

Speaker spotlight #3: Kelly Zhang, Imperial College London. Can we build valid confidence intervals for the average reward of adaptive bandit algorithms? Kelly will present Bandit Simulation for Inference, a framework for inference with on-policy or off-policy bandit data.

AAE Workshop application deadline is in 2 weeks — have you applied yet? Join us at Gatsby Unit on June 18–19 for two days on adaptive experimentation, causal inference, bandits, and RL. Apply here: aae-workshop.github.io/info/ #AdaptiveExperimentation #CausalInference #Bandits #RL

Speaker spotlight #2: Aurélien Bibaut, @netflix.com. Can policy-based contextual bandits achieve fast regret without realizability? Aurélien will explore this at AAE through variance-aware pessimistic policy learning and self-normalized martingale tools for adaptive data.

Speaker spotlight #1: Tor Lattimore, DeepMind. What can continuous-time diffusions teach us about RL, ML, and adaptive experimentation? Tor will explore this at AAE through sequential design and policy gradients for stochastic bandits.

The AAE Workshop deadline is in 3 weeks — have you applied yet? 📅 June 18–19 📍 Gatsby Computational Neuroscience Unit, London Join us for two days on causal inference, adaptive experiments, bandits, and RL. 🔗 t.co/Zar0qWhgA8

🚀 Excited to announce the Advances in Adaptive Experimentation (AAE) Workshop! 📅 June 18–19 🔗 t.co/Zar0qWhgA8 Join us at @gatsbyucl.bsky.social in London for two days at the frontier of causal inference 🧩, adaptive experiments 🔁, and bandits/RL 🤖!