Yuki Minai·4d agoModel-free methods for prioritizing the brain stimulation parameter space in a smart wayIn the first post of this series, we reviewed three broad approaches for updating stimulation parameters over time, model-free methods…
Ashutosh Singhal·Aug 18A perfect model can’t stop your self-driving lab from running a doomed synthesis. I built the gate..What building an autonomous materials-discovery loop taught me: the durable value is not the surrogate, it is the deterministic safety ga..
Outermostkt·Jul 14Is Bayes Just… Not a Thing in English?I’m Japanese, and I’m personally really into Bayesian statistics. I wrote and published an article about it… but literally nobody’s reading…
A. Belantari·Jun 10Reinforcement Learning- Goal-Based Bayesian Optimization: An exampleA combination of a chaotic environment, a continuous reinforcement‑learning agent, a deep learning algorithm, a moving probabilistic…
Mark Shipman·May 19How to Scale Optuna Without Breaking Bayesian OptimizationOptuna is excellent for hyperparameter optimization, but the naive way to scale it can quietly undermine the very thing that makes Bayesian…
shashank Jain·Mar 29Karpathy Auto research vs Bayesian OptimizationAutonomous research loops are becoming a powerful way to think about how AI systems can improve models with minimal human intervention. One…
Learner·Mar 25Hyperparameter Tuning: Optimizing Machine Learning Models for Best PerformanceHello everyone 👋
Kürşat Kaya·Nov 11, 2025Optimize Hyperparameters Smarter and Faster with TabPFNYou launch a model, tweak a few hyperparameters, and hit “run.” Hours later, your GPU is still humming, and your model barely improves. You…
Indigo Shadow·Oct 9, 2025When AI Spills Its Secrets: Model Inversion Attacks (Hacking AI Part 3)Model inversion is an attack on AI systems where an attacker attempts to reconstruct or infer sensitive information about the model’s…
